dogs vs cat

import zipfile, os, shutil, re
from os.path import isfile, isdir
import random
from tqdm import tqdm
import cv2
import numpy as np
from keras.preprocessing import image
from keras.applications.inception_v3 import InceptionV3
from keras.applications.inception_v3 import preprocess_input as inception_input
from keras.applications.resnet50 import ResNet50,decode_predictions
from keras.applications.resnet50 import preprocess_input as resnet_input
from keras.applications.xception import Xception
# from keras.preprocessing.image import ImageDataGenerator
from keras import optimizers
from keras.models import Model
# from keras.models import Sequential
from keras.layers import Convolution2D, MaxPooling2D, Activation, Dropout, Flatten, Dense,GlobalAveragePooling2D,Input
from keras.callbacks import EarlyStopping, ModelCheckpoint, CSVLogger

import matplotlib.pyplot as plt
import matplotlib.image as mpimg
%matplotlib inline

# extract train.zip image to folder 'train'
if not isdir('train'):
    zipFile = zipfile.ZipFile('train.zip')
    zipFile.extractall()
    zipFile.close()
    
# move cat's image to folder 'train/cat', dog's image to folder 'train/dog'
if not isdir('train/cat'):
    os.mkdir('train/cat')        # create folder train/cat
if not isdir('train/dog'):
    os.mkdir('train/dog')        # create folder train/dog
    
# search files in train folder, check whether it match cat or dog
for filename in os.listdir('train'):
    match_cat = re.search(r'cat.[0-9]*.jpg',filename)
    if match_cat:           # if filename including cat then move to folder train/cat
        shutil.move('train/'+filename, 'train/cat/')   
    
    match_dog = re.search(r'dog.[0-9]*.jpg',filename)
    if match_dog:           # if filename including dog then move to folder train/dog
        shutil.move('train/'+filename, 'train/dog/'+filename)
        
# extract test.zip image to folder 'test'
if not isdir('test'):
    zipFile = zipfile.ZipFile('test.zip')
    zipFile.extractall()
    zipFile.close()
    
if not isdir('test/test'):
    os.mkdir('test/test')        # if not exist test/test then create the sub-folder 'test/test'
    for filename in os.listdir('test'):      # search files in 'test', then move to sub-folder 'test/test'
        if not os.path.isdir(filename):      
            shutil.move('test/'+filename,'test/test/')

C:\Users\thomas_gui\AppData\Local\conda\conda\envs\py36\lib\site-packages\h5py\__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
Using TensorFlow backend.

# Show cat picture of train
fig1 = plt.figure(figsize=(20,10))  # figure size=(20,10)
for i in range(10):
    img = mpimg.imread('train/cat/cat.%i.jpg'%i)
    print('cat.%i.jpg:'%i, 'dimension', img.shape)
    plt.subplot(2,5,i+1)
    plt.title('cat.%i.jpg'%i)
    plt.imshow(img)
plt.show()

# show dog picture of train
fig2 = plt.figure(figsize=(20,10))  # figure size=(20,10)
for i in range(10):
    img = mpimg.imread('train/dog/dog.%i.jpg'%i)
    print('dog.%i.jpg:'%i, 'dimension', img.shape)
    plt.subplot(2,5,i+1)
    plt.title('dog.%i.jpg'%i)
    plt.imshow(img)
plt.show()

cat.0.jpg: dimension (374, 500, 3)
cat.1.jpg: dimension (280, 300, 3)
cat.2.jpg: dimension (396, 312, 3)
cat.3.jpg: dimension (414, 500, 3)
cat.4.jpg: dimension (375, 499, 3)
cat.5.jpg: dimension (144, 175, 3)
cat.6.jpg: dimension (303, 400, 3)
cat.7.jpg: dimension (499, 495, 3)
cat.8.jpg: dimension (345, 461, 3)
cat.9.jpg: dimension (425, 320, 3)

dog.0.jpg: dimension (375, 499, 3)
dog.1.jpg: dimension (499, 327, 3)
dog.2.jpg: dimension (199, 187, 3)
dog.3.jpg: dimension (375, 499, 3)
dog.4.jpg: dimension (287, 300, 3)
dog.5.jpg: dimension (376, 499, 3)
dog.6.jpg: dimension (488, 499, 3)
dog.7.jpg: dimension (264, 299, 3)
dog.8.jpg: dimension (500, 469, 3)
dog.9.jpg: dimension (500, 368, 3)

# show test picture
fig3 = plt.figure(figsize=(20,10))  # figure size=(20,10)
for i in range(10):
    i +=1
    img = mpimg.imread('test/test/%i.jpg'%i)
    print('%i.jpg:'%i, 'dimension', img.shape)
    plt.subplot(2,5,i)
    plt.title('%i.jpg'%i)
    plt.imshow(img)
plt.show()

1.jpg: dimension (499, 381, 3)
2.jpg: dimension (299, 296, 3)
3.jpg: dimension (299, 300, 3)
4.jpg: dimension (288, 374, 3)
5.jpg: dimension (400, 399, 3)
6.jpg: dimension (375, 499, 3)
7.jpg: dimension (148, 192, 3)
8.jpg: dimension (234, 325, 3)
9.jpg: dimension (380, 480, 3)
10.jpg: dimension (374, 500, 3)

# from imagenet, dogs class, cats class list
dogs = [
 'n02085620','n02085782','n02085936','n02086079'
,'n02086240','n02086646','n02086910','n02087046'
,'n02087394','n02088094','n02088238','n02088364'
,'n02088466','n02088632','n02089078','n02089867'
,'n02089973','n02090379','n02090622','n02090721'
,'n02091032','n02091134','n02091244','n02091467'
,'n02091635','n02091831','n02092002','n02092339'
,'n02093256','n02093428','n02093647','n02093754'
,'n02093859','n02093991','n02094114','n02094258'
,'n02094433','n02095314','n02095570','n02095889'
,'n02096051','n02096177','n02096294','n02096437'
,'n02096585','n02097047','n02097130','n02097209'
,'n02097298','n02097474','n02097658','n02098105'
,'n02098286','n02098413','n02099267','n02099429'
,'n02099601','n02099712','n02099849','n02100236'
,'n02100583','n02100735','n02100877','n02101006'
,'n02101388','n02101556','n02102040','n02102177'
,'n02102318','n02102480','n02102973','n02104029'
,'n02104365','n02105056','n02105162','n02105251'
,'n02105412','n02105505','n02105641','n02105855'
,'n02106030','n02106166','n02106382','n02106550'
,'n02106662','n02107142','n02107312','n02107574'
,'n02107683','n02107908','n02108000','n02108089'
,'n02108422','n02108551','n02108915','n02109047'
,'n02109525','n02109961','n02110063','n02110185'
,'n02110341','n02110627','n02110806','n02110958'
,'n02111129','n02111277','n02111500','n02111889'
,'n02112018','n02112137','n02112350','n02112706'
,'n02113023','n02113186','n02113624','n02113712'
,'n02113799','n02113978']

cats=[
'n02123045','n02123159','n02123394','n02123597'
,'n02124075','n02125311','n02127052']

# generate batchs for ResNet50 predict_generator
def test_gen_224(X, batch_size): 
    
    datalen = len(X)
    counter = datalen//batch_size
    while (True):
        
        for i in range(counter):
            X_224 = np.zeros((batch_size,224,224,3),dtype = np.float)
            for j in range(batch_size):
                X_224[j] = cv2.resize(cv2.imread(X[i* batch_size+j]),(224,224))
                
            X_224 = resnet_input(X_224)
            yield X_224

# use ResNet50 to predict picture class
# add non cat picture to cat_outlier list
# add non dog picture to dog_outlier list
# cat and dog train file list
X_catfile = ['train/cat/cat.%d.jpg' % i for i in range(12500)]
X_dogfile = ['train/dog/dog.%d.jpg' % i for i in range(12500)]

model = ResNet50(weights='imagenet')
cat_preds = model.predict_generator(test_gen_224(X_catfile,100),steps=125)
dog_preds = model.predict_generator(test_gen_224(X_dogfile,100),steps=125)

cat_outlier = []
dog_outlier = []
for i in tqdm(range(12500)):
    iscat = False
    isdog = False
    cat_prediction = decode_predictions(cat_preds[i:(i+1),:], top=30)[0]
    dog_prediction = decode_predictions(dog_preds[i:(i+1),:], top=30)[0] 
    for j in range(30):
        if cat_prediction[j][0] in cats:
            iscat = True
            break
    for j in range(30):        
        if dog_prediction[j][0] in dogs:
            isdog = True
            break
            
    if not iscat:
        cat_outlier.append(X_catfile[i])     # append cat picture outlier to list
    if not isdog:
        dog_outlier.append(X_dogfile[i])     # append cat picture outlier to list

# print('Number of outliers for cat: ',len(cat_outlier))
# print('Number of outliers for dog: ',len(dog_outlier))

100%|██████████████████████████████████████████████████████████████████████████| 12500/12500 [00:01<00:00, 6876.19it/s]

# use InceptionV3 to predict picture class
# choose non cat or non dog picture from previous list

cat_outlier1 = []
dog_outlier1 = []
model = InceptionV3(weights='imagenet')

for i in tqdm(range(len(cat_outlier))):
    img = image.load_img(cat_outlier[i], target_size=(299, 299))
    x = image.img_to_array(img)
    x = np.expand_dims(x, axis=0)
    x = inception_input(x)
    cat_preds = model.predict(x)
    cat_prediction = decode_predictions(cat_preds, top=30)[0]
    
    iscat = False
    for j in range(30):
        if cat_prediction[j][0] in cats:
            iscat = True
            break
    if not iscat:
        cat_outlier1.append(cat_outlier[i])

for i in tqdm(range(len(dog_outlier))):
    img = image.load_img(dog_outlier[i], target_size=(299, 299))
    x = image.img_to_array(img)
    x = np.expand_dims(x, axis=0)
    x = inception_input(x)
    dog_preds = model.predict(x)
    dog_prediction = decode_predictions(dog_preds, top=30)[0]
    
    isdog = False
    for j in range(30):
        if dog_prediction[j][0] in dogs:
            isdog = True
            break
    if not isdog:
        dog_outlier1.append(dog_outlier[i])
        
# print('Number of outliers for cat: ',len(cat_outlier1))
# print('Number of outliers for dog: ',len(dog_outlier1))

330
56

100%|████████████████████████████████████████████████████████████████████████████████| 330/330 [00:10<00:00, 30.35it/s]
100%|██████████████████████████████████████████████████████████████████████████████████| 56/56 [00:01<00:00, 32.29it/s]

84
21

# use Xception to predict picture class
# choose non cat or non dog picture from previous list

cat_outlier = []
dog_outlier = []
model = Xception(weights='imagenet')

for i in tqdm(range(len(cat_outlier1))):
    img = image.load_img(cat_outlier1[i], target_size=(299, 299))
    x = image.img_to_array(img)
    x = np.expand_dims(x, axis=0)
    x = inception_input(x)
    cat_preds = model.predict(x)
    cat_prediction = decode_predictions(cat_preds, top=30)[0]
    
    iscat = False
    for j in range(30):
        if cat_prediction[j][0] in cats:
            iscat = True
            break
    if not iscat:
        cat_outlier.append(cat_outlier1[i])

for i in tqdm(range(len(dog_outlier1))):
    img = image.load_img(dog_outlier1[i], target_size=(299, 299))
    x = image.img_to_array(img)
    x = np.expand_dims(x, axis=0)
    x = inception_input(x)
    dog_preds = model.predict(x)
    dog_prediction = decode_predictions(dog_preds, top=30)[0]
    
    isdog = False
    for j in range(30):
        if dog_prediction[j][0] in dogs:
            isdog = True
            break
    if not isdog:
        dog_outlier.append(dog_outlier1[i])
        
# print('Number of outliers for cat: ',len(cat_outlier))
# print('Number of outliers for dog: ',len(dog_outlier))

100%|██████████████████████████████████████████████████████████████████████████████████| 84/84 [00:02<00:00, 28.88it/s]
100%|██████████████████████████████████████████████████████████████████████████████████| 21/21 [00:00<00:00, 35.87it/s]

print('Number of outliers for cat: ',len(cat_outlier))

# print('non cat list:\n',cat_outlier)
fig1 = plt.figure(figsize=(20,40))  # figure size=(20,10)
for i in range(len(cat_outlier)):
    img = mpimg.imread(cat_outlier[i])
    plt.subplot(10,5,i+1)
    plt.title(cat_outlier[i])
    plt.imshow(img)
plt.show()

Number of outliers for cat:  46

print('Number of outliers for dog: ',len(dog_outlier))

fig2 = plt.figure(figsize=(20,20))  # figure size=(20,10)
for i in range(len(dog_outlier)):
    img = mpimg.imread(dog_outlier[i])
    plt.subplot(4,5,i+1)
    plt.title(dog_outlier[i])
    plt.imshow(img)
plt.show()

Number of outliers for cat:  18

# define random_transfer function
# used these functions for data argumentation

def random_crop(img, ratio=1.0):
    #随机剪裁, Ratio是裁剪后与裁剪前的面积比
    if random.random() < 1:
        h,w = img.shape[:2]
        #长宽比随机扰动变量 hw_delta
        hw_delta = np.random.uniform(-0.05,0.05)
        hw_mult = 1 + hw_delta
        
        w_crop = int(round(w*np.sqrt(ratio*hw_mult)))
        
        if w_crop > w:
            w_crop = w
        
        h_crop = int(round(h*np.sqrt(ratio/hw_mult)))
        if h_crop > h:
            h_crop = h
        
        x0 = np.random.randint(0,w-w_crop+1)
        y0 = np.random.randint(0,h-h_crop+1)
        
        img = img[y0:y0+h_crop,x0:x0+w_crop]
        
    return img
    
def random_rotate(img, angle=0.0):
    if random.random() < 1:
        h,w = img.shape[:2]
        # angle = np.random.uniform(-angle,angle)
        # angle cycle is 360
        angle %= 360
        # 用openCV 内置函数计算仿射矩阵
        M_rotate = cv2.getRotationMatrix2D((w/2,h/2),angle,1)
        # 得到旋转后的图片
        img = cv2.warpAffine(img, M_rotate, (w, h))
        angle_crop = angle % 180
        
        if angle_crop > 90:
            angle_crop = 180 - angle_crop
        # convert to rad
        theta = angle_crop * np.pi / 180.0
        # compute high width ratio
        hw_ratio = float(h) / float(w)
        
        tan_theta = np.tan(theta)
        numerator = np.cos(theta) + np.sin(theta) * tan_theta
        
        # 计算分母项中的宽高比相关的项
        r = hw_ratio if h > w else 1/hw_ratio
        # 计算分母项
        denominator = r * tan_theta +1
        # 计算最终边长系数
        crop_mult = numerator / denominator
        # 得到剪裁区域
        w_crop = int(round(crop_mult*w))
        h_crop = int(round(crop_mult*h))
        x0 = int((w-w_crop)/2)
        y0 = int((h-h_crop)/2)
        img = img[y0:y0+h_crop,x0:x0+w_crop]
    return img

def random_shear(img,angle=0.0):
    if random.random() < 1:
        h,w = img.shape[:2]
        #产生随机剪切角度值
        # angle = np.random.uniform(-angle,angle)
        # x轴剪切变换，角度值=angle
        theta = angle * np.pi / 180
        M_shear = np.array([[1,np.tan(theta), 0],[0,1,0]],dtype = np.float32)
        img = cv2.warpAffine(img, M_shear, (w, h))
    return img

def random_h_flip(img, horizontal_flip=False):
    if horizontal_flip == True:
        if random.random() < 1:
            img = cv2.flip(img, 1)
    return img
            
def random_v_flip(img, vertical_flip=False):
    if vertical_flip == True:
        if random.random() < 1:
            img = cv2.flip(img,0)
    return img    

def random_transfer(img, ratio=None,rotate=None,shear=None,
                  horizontal_flip=False,vertical_flip=False):
    params = {}
    if ratio is not None:
        params['ratio'] = ratio
    if rotate is not None:
        params['rotate'] = rotate
    if shear is not None:
        params['shear'] = shear
    if horizontal_flip:
        params['horizontal_flip'] = horizontal_flip
    if vertical_flip:
        params['vertical_flip'] = vertical_flip
        
    if params:
        func = []
        for param in params.keys():
            func.append(param)
    func = random.choice(func)
    # print(func,params[func])
    
    function_map = { 'ratio':random_crop,
                     'rotate':random_rotate,
                     'shear':random_shear,
                     'horizontal_flip':random_h_flip,
                     'vertical_flip':random_v_flip
                    }
    
    img_transfer = function_map[func](img,params[func])
    return img_transfer

# random choose a existing image, excute random transfer, replace each outlier image
for i in range(len(cat_outlier)):
    cat_file = random.choice(X_catfile)
    img_cat = cv2.imread(cat_file)
    img_cat = random_transfer(img_cat, 0.9,10,10,True,True)
    cv2.imwrite(cat_outlier[i],img_cat)
    
for i in range(len(dog_outlier)):
    dog_file = random.choice(X_dogfile)
    img_dog = cv2.imread(dog_file)
    img_dog = random_transfer(img_dog, 0.9,10,10,True,True)
    cv2.imwrite(dog_outlier[i],img_dog)

X_catfile = ['train/cat/cat.%d.jpg' % i for i in range(12500)]
X_dogfile = ['train/dog/dog.%d.jpg' % i for i in range(12500)]
# set the validation split = 0.2
# then split train_set into X_train,X_val, y_train, y_val
splitpoint = int(12500 * 0.8)
# to keep cat and dog file samples balance in train, validation set.
# split 10,000 cat file list into train, 2,500 cat file list into validation
X_catfile_train,X_catfile_val = X_catfile[:splitpoint],X_catfile[splitpoint:]
# split 10,000 dog file list into train, 2,500 dog file list into validation
X_dogfile_train,X_dogfile_val = X_dogfile[:splitpoint],X_dogfile[splitpoint:]
# merge cat and dog train set, total 20,000 file list, first 10,000 is cat file, next 10,000 is dog file
X_train = np.array(X_catfile_train + X_dogfile_train)
# generate train label, first 10,000 is cat file, label = 0 , then next 10,000 label = 1

y_train = np.array([0 for i in range(splitpoint)] + [1 for i in range(splitpoint)])
# same as above operation, merge cat cat and dog validation set, then generate validation label
X_val = np.array(X_catfile_val + X_dogfile_val)
y_val = np.array([0 for i in range(splitpoint,12500)] + [1 for i in range(splitpoint,12500)])

# shuffle train & validation set
# set index for train and validation set
train_idx = np.arange(20000)
val_idx = np.arange(5000)
# set random seed to make sure shuffle result not change everytime
random.seed(2018)
# shuffle train index
random.shuffle(train_idx)

random.seed(2018)
# shuffle validation index
random.shuffle(val_idx)
# re-arrange X_train,y_train by shuffled index
X_train,y_train = X_train[train_idx],y_train[train_idx]
X_val,y_val = X_val[val_idx],y_val[val_idx]
#print(y_train.sum())    #half sample list is cat，another one is dog, so train label sum = 10,000

batch_size = 50
epochs = 10

# define train_generator function, yield batchs of train and validation data 
def train_generator(X, y, batch_size): 
    
    datalen = len(y)
    counter = datalen//batch_size
    while (True):
        
        for i in range(counter):
            X_299 = np.zeros((batch_size,299,299,3),dtype = np.float)
            for j in range(batch_size):
                X_299[j] = cv2.resize(cv2.imread(X[i* batch_size+j]),(299,299))
                
            X_299 = inception_input(X_299)
            yield X_299, y[i * batch_size:(i + 1) * batch_size]

def val_generator(X, y, batch_size):
    
    datalen = len(y)
    counter = datalen//batch_size
    while (True):
        
        for i in range(counter):
            X_299 = np.zeros((batch_size,299,299,3),dtype = np.float)
            for j in range(batch_size):
                X_299[j] = cv2.resize(cv2.imread(X[i* batch_size+j]),(299,299))
                
            X_299 = inception_input(X_299)
            yield X_299, y[i * batch_size:(i + 1) * batch_size]

# from IPython.display import SVG
# from keras.utils.vis_utils import model_to_dot
# from keras.utils import plot_model

model_InceptionV3 = InceptionV3(include_top = False, weights = 'imagenet', input_shape=(299,299,3))
for layer in model_InceptionV3.layers:
    layer.trainable = False
model = GlobalAveragePooling2D() (model_InceptionV3.output)

model = Dropout(0.5)(model)
model = Dense(1, activation='sigmoid')(model)
model_InceptionV3 = Model(model_InceptionV3.input,model, name = 'model_InceptionV3')

# plot_model(model_InceptionV3_GAP, to_file='model_InceptionV3.png',show_shapes = True) 
# SVG(model_to_dot(model_InceptionV3).create(prog='dot', format='svg'))

model_InceptionV3.summary()

__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_3 (InputLayer)            (None, 299, 299, 3)  0                                            
__________________________________________________________________________________________________
conv2d_189 (Conv2D)             (None, 149, 149, 32) 864         input_3[0][0]                    
__________________________________________________________________________________________________
batch_normalization_189 (BatchN (None, 149, 149, 32) 96          conv2d_189[0][0]                 
__________________________________________________________________________________________________
activation_189 (Activation)     (None, 149, 149, 32) 0           batch_normalization_189[0][0]    
__________________________________________________________________________________________________
conv2d_190 (Conv2D)             (None, 147, 147, 32) 9216        activation_189[0][0]             
__________________________________________________________________________________________________
batch_normalization_190 (BatchN (None, 147, 147, 32) 96          conv2d_190[0][0]                 
__________________________________________________________________________________________________
activation_190 (Activation)     (None, 147, 147, 32) 0           batch_normalization_190[0][0]    
__________________________________________________________________________________________________
conv2d_191 (Conv2D)             (None, 147, 147, 64) 18432       activation_190[0][0]             
__________________________________________________________________________________________________
batch_normalization_191 (BatchN (None, 147, 147, 64) 192         conv2d_191[0][0]                 
__________________________________________________________________________________________________
activation_191 (Activation)     (None, 147, 147, 64) 0           batch_normalization_191[0][0]    
__________________________________________________________________________________________________
max_pooling2d_9 (MaxPooling2D)  (None, 73, 73, 64)   0           activation_191[0][0]             
__________________________________________________________________________________________________
conv2d_192 (Conv2D)             (None, 73, 73, 80)   5120        max_pooling2d_9[0][0]            
__________________________________________________________________________________________________
batch_normalization_192 (BatchN (None, 73, 73, 80)   240         conv2d_192[0][0]                 
__________________________________________________________________________________________________
activation_192 (Activation)     (None, 73, 73, 80)   0           batch_normalization_192[0][0]    
__________________________________________________________________________________________________
conv2d_193 (Conv2D)             (None, 71, 71, 192)  138240      activation_192[0][0]             
__________________________________________________________________________________________________
batch_normalization_193 (BatchN (None, 71, 71, 192)  576         conv2d_193[0][0]                 
__________________________________________________________________________________________________
activation_193 (Activation)     (None, 71, 71, 192)  0           batch_normalization_193[0][0]    
__________________________________________________________________________________________________
max_pooling2d_10 (MaxPooling2D) (None, 35, 35, 192)  0           activation_193[0][0]             
__________________________________________________________________________________________________
conv2d_197 (Conv2D)             (None, 35, 35, 64)   12288       max_pooling2d_10[0][0]           
__________________________________________________________________________________________________
batch_normalization_197 (BatchN (None, 35, 35, 64)   192         conv2d_197[0][0]                 
__________________________________________________________________________________________________
activation_197 (Activation)     (None, 35, 35, 64)   0           batch_normalization_197[0][0]    
__________________________________________________________________________________________________
conv2d_195 (Conv2D)             (None, 35, 35, 48)   9216        max_pooling2d_10[0][0]           
__________________________________________________________________________________________________
conv2d_198 (Conv2D)             (None, 35, 35, 96)   55296       activation_197[0][0]             
__________________________________________________________________________________________________
batch_normalization_195 (BatchN (None, 35, 35, 48)   144         conv2d_195[0][0]                 
__________________________________________________________________________________________________
batch_normalization_198 (BatchN (None, 35, 35, 96)   288         conv2d_198[0][0]                 
__________________________________________________________________________________________________
activation_195 (Activation)     (None, 35, 35, 48)   0           batch_normalization_195[0][0]    
__________________________________________________________________________________________________
activation_198 (Activation)     (None, 35, 35, 96)   0           batch_normalization_198[0][0]    
__________________________________________________________________________________________________
average_pooling2d_19 (AveragePo (None, 35, 35, 192)  0           max_pooling2d_10[0][0]           
__________________________________________________________________________________________________
conv2d_194 (Conv2D)             (None, 35, 35, 64)   12288       max_pooling2d_10[0][0]           
__________________________________________________________________________________________________
conv2d_196 (Conv2D)             (None, 35, 35, 64)   76800       activation_195[0][0]             
__________________________________________________________________________________________________
conv2d_199 (Conv2D)             (None, 35, 35, 96)   82944       activation_198[0][0]             
__________________________________________________________________________________________________
conv2d_200 (Conv2D)             (None, 35, 35, 32)   6144        average_pooling2d_19[0][0]       
__________________________________________________________________________________________________
batch_normalization_194 (BatchN (None, 35, 35, 64)   192         conv2d_194[0][0]                 
__________________________________________________________________________________________________
batch_normalization_196 (BatchN (None, 35, 35, 64)   192         conv2d_196[0][0]                 
__________________________________________________________________________________________________
batch_normalization_199 (BatchN (None, 35, 35, 96)   288         conv2d_199[0][0]                 
__________________________________________________________________________________________________
batch_normalization_200 (BatchN (None, 35, 35, 32)   96          conv2d_200[0][0]                 
__________________________________________________________________________________________________
activation_194 (Activation)     (None, 35, 35, 64)   0           batch_normalization_194[0][0]    
__________________________________________________________________________________________________
activation_196 (Activation)     (None, 35, 35, 64)   0           batch_normalization_196[0][0]    
__________________________________________________________________________________________________
activation_199 (Activation)     (None, 35, 35, 96)   0           batch_normalization_199[0][0]    
__________________________________________________________________________________________________
activation_200 (Activation)     (None, 35, 35, 32)   0           batch_normalization_200[0][0]    
__________________________________________________________________________________________________
mixed0 (Concatenate)            (None, 35, 35, 256)  0           activation_194[0][0]             
                                                                 activation_196[0][0]             
                                                                 activation_199[0][0]             
                                                                 activation_200[0][0]             
__________________________________________________________________________________________________
conv2d_204 (Conv2D)             (None, 35, 35, 64)   16384       mixed0[0][0]                     
__________________________________________________________________________________________________
batch_normalization_204 (BatchN (None, 35, 35, 64)   192         conv2d_204[0][0]                 
__________________________________________________________________________________________________
activation_204 (Activation)     (None, 35, 35, 64)   0           batch_normalization_204[0][0]    
__________________________________________________________________________________________________
conv2d_202 (Conv2D)             (None, 35, 35, 48)   12288       mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_205 (Conv2D)             (None, 35, 35, 96)   55296       activation_204[0][0]             
__________________________________________________________________________________________________
batch_normalization_202 (BatchN (None, 35, 35, 48)   144         conv2d_202[0][0]                 
__________________________________________________________________________________________________
batch_normalization_205 (BatchN (None, 35, 35, 96)   288         conv2d_205[0][0]                 
__________________________________________________________________________________________________
activation_202 (Activation)     (None, 35, 35, 48)   0           batch_normalization_202[0][0]    
__________________________________________________________________________________________________
activation_205 (Activation)     (None, 35, 35, 96)   0           batch_normalization_205[0][0]    
__________________________________________________________________________________________________
average_pooling2d_20 (AveragePo (None, 35, 35, 256)  0           mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_201 (Conv2D)             (None, 35, 35, 64)   16384       mixed0[0][0]                     
__________________________________________________________________________________________________
conv2d_203 (Conv2D)             (None, 35, 35, 64)   76800       activation_202[0][0]             
__________________________________________________________________________________________________
conv2d_206 (Conv2D)             (None, 35, 35, 96)   82944       activation_205[0][0]             
__________________________________________________________________________________________________
conv2d_207 (Conv2D)             (None, 35, 35, 64)   16384       average_pooling2d_20[0][0]       
__________________________________________________________________________________________________
batch_normalization_201 (BatchN (None, 35, 35, 64)   192         conv2d_201[0][0]                 
__________________________________________________________________________________________________
batch_normalization_203 (BatchN (None, 35, 35, 64)   192         conv2d_203[0][0]                 
__________________________________________________________________________________________________
batch_normalization_206 (BatchN (None, 35, 35, 96)   288         conv2d_206[0][0]                 
__________________________________________________________________________________________________
batch_normalization_207 (BatchN (None, 35, 35, 64)   192         conv2d_207[0][0]                 
__________________________________________________________________________________________________
activation_201 (Activation)     (None, 35, 35, 64)   0           batch_normalization_201[0][0]    
__________________________________________________________________________________________________
activation_203 (Activation)     (None, 35, 35, 64)   0           batch_normalization_203[0][0]    
__________________________________________________________________________________________________
activation_206 (Activation)     (None, 35, 35, 96)   0           batch_normalization_206[0][0]    
__________________________________________________________________________________________________
activation_207 (Activation)     (None, 35, 35, 64)   0           batch_normalization_207[0][0]    
__________________________________________________________________________________________________
mixed1 (Concatenate)            (None, 35, 35, 288)  0           activation_201[0][0]             
                                                                 activation_203[0][0]             
                                                                 activation_206[0][0]             
                                                                 activation_207[0][0]             
__________________________________________________________________________________________________
conv2d_211 (Conv2D)             (None, 35, 35, 64)   18432       mixed1[0][0]                     
__________________________________________________________________________________________________
batch_normalization_211 (BatchN (None, 35, 35, 64)   192         conv2d_211[0][0]                 
__________________________________________________________________________________________________
activation_211 (Activation)     (None, 35, 35, 64)   0           batch_normalization_211[0][0]    
__________________________________________________________________________________________________
conv2d_209 (Conv2D)             (None, 35, 35, 48)   13824       mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_212 (Conv2D)             (None, 35, 35, 96)   55296       activation_211[0][0]             
__________________________________________________________________________________________________
batch_normalization_209 (BatchN (None, 35, 35, 48)   144         conv2d_209[0][0]                 
__________________________________________________________________________________________________
batch_normalization_212 (BatchN (None, 35, 35, 96)   288         conv2d_212[0][0]                 
__________________________________________________________________________________________________
activation_209 (Activation)     (None, 35, 35, 48)   0           batch_normalization_209[0][0]    
__________________________________________________________________________________________________
activation_212 (Activation)     (None, 35, 35, 96)   0           batch_normalization_212[0][0]    
__________________________________________________________________________________________________
average_pooling2d_21 (AveragePo (None, 35, 35, 288)  0           mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_208 (Conv2D)             (None, 35, 35, 64)   18432       mixed1[0][0]                     
__________________________________________________________________________________________________
conv2d_210 (Conv2D)             (None, 35, 35, 64)   76800       activation_209[0][0]             
__________________________________________________________________________________________________
conv2d_213 (Conv2D)             (None, 35, 35, 96)   82944       activation_212[0][0]             
__________________________________________________________________________________________________
conv2d_214 (Conv2D)             (None, 35, 35, 64)   18432       average_pooling2d_21[0][0]       
__________________________________________________________________________________________________
batch_normalization_208 (BatchN (None, 35, 35, 64)   192         conv2d_208[0][0]                 
__________________________________________________________________________________________________
batch_normalization_210 (BatchN (None, 35, 35, 64)   192         conv2d_210[0][0]                 
__________________________________________________________________________________________________
batch_normalization_213 (BatchN (None, 35, 35, 96)   288         conv2d_213[0][0]                 
__________________________________________________________________________________________________
batch_normalization_214 (BatchN (None, 35, 35, 64)   192         conv2d_214[0][0]                 
__________________________________________________________________________________________________
activation_208 (Activation)     (None, 35, 35, 64)   0           batch_normalization_208[0][0]    
__________________________________________________________________________________________________
activation_210 (Activation)     (None, 35, 35, 64)   0           batch_normalization_210[0][0]    
__________________________________________________________________________________________________
activation_213 (Activation)     (None, 35, 35, 96)   0           batch_normalization_213[0][0]    
__________________________________________________________________________________________________
activation_214 (Activation)     (None, 35, 35, 64)   0           batch_normalization_214[0][0]    
__________________________________________________________________________________________________
mixed2 (Concatenate)            (None, 35, 35, 288)  0           activation_208[0][0]             
                                                                 activation_210[0][0]             
                                                                 activation_213[0][0]             
                                                                 activation_214[0][0]             
__________________________________________________________________________________________________
conv2d_216 (Conv2D)             (None, 35, 35, 64)   18432       mixed2[0][0]                     
__________________________________________________________________________________________________
batch_normalization_216 (BatchN (None, 35, 35, 64)   192         conv2d_216[0][0]                 
__________________________________________________________________________________________________
activation_216 (Activation)     (None, 35, 35, 64)   0           batch_normalization_216[0][0]    
__________________________________________________________________________________________________
conv2d_217 (Conv2D)             (None, 35, 35, 96)   55296       activation_216[0][0]             
__________________________________________________________________________________________________
batch_normalization_217 (BatchN (None, 35, 35, 96)   288         conv2d_217[0][0]                 
__________________________________________________________________________________________________
activation_217 (Activation)     (None, 35, 35, 96)   0           batch_normalization_217[0][0]    
__________________________________________________________________________________________________
conv2d_215 (Conv2D)             (None, 17, 17, 384)  995328      mixed2[0][0]                     
__________________________________________________________________________________________________
conv2d_218 (Conv2D)             (None, 17, 17, 96)   82944       activation_217[0][0]             
__________________________________________________________________________________________________
batch_normalization_215 (BatchN (None, 17, 17, 384)  1152        conv2d_215[0][0]                 
__________________________________________________________________________________________________
batch_normalization_218 (BatchN (None, 17, 17, 96)   288         conv2d_218[0][0]                 
__________________________________________________________________________________________________
activation_215 (Activation)     (None, 17, 17, 384)  0           batch_normalization_215[0][0]    
__________________________________________________________________________________________________
activation_218 (Activation)     (None, 17, 17, 96)   0           batch_normalization_218[0][0]    
__________________________________________________________________________________________________
max_pooling2d_11 (MaxPooling2D) (None, 17, 17, 288)  0           mixed2[0][0]                     
__________________________________________________________________________________________________
mixed3 (Concatenate)            (None, 17, 17, 768)  0           activation_215[0][0]             
                                                                 activation_218[0][0]             
                                                                 max_pooling2d_11[0][0]           
__________________________________________________________________________________________________
conv2d_223 (Conv2D)             (None, 17, 17, 128)  98304       mixed3[0][0]                     
__________________________________________________________________________________________________
batch_normalization_223 (BatchN (None, 17, 17, 128)  384         conv2d_223[0][0]                 
__________________________________________________________________________________________________
activation_223 (Activation)     (None, 17, 17, 128)  0           batch_normalization_223[0][0]    
__________________________________________________________________________________________________
conv2d_224 (Conv2D)             (None, 17, 17, 128)  114688      activation_223[0][0]             
__________________________________________________________________________________________________
batch_normalization_224 (BatchN (None, 17, 17, 128)  384         conv2d_224[0][0]                 
__________________________________________________________________________________________________
activation_224 (Activation)     (None, 17, 17, 128)  0           batch_normalization_224[0][0]    
__________________________________________________________________________________________________
conv2d_220 (Conv2D)             (None, 17, 17, 128)  98304       mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_225 (Conv2D)             (None, 17, 17, 128)  114688      activation_224[0][0]             
__________________________________________________________________________________________________
batch_normalization_220 (BatchN (None, 17, 17, 128)  384         conv2d_220[0][0]                 
__________________________________________________________________________________________________
batch_normalization_225 (BatchN (None, 17, 17, 128)  384         conv2d_225[0][0]                 
__________________________________________________________________________________________________
activation_220 (Activation)     (None, 17, 17, 128)  0           batch_normalization_220[0][0]    
__________________________________________________________________________________________________
activation_225 (Activation)     (None, 17, 17, 128)  0           batch_normalization_225[0][0]    
__________________________________________________________________________________________________
conv2d_221 (Conv2D)             (None, 17, 17, 128)  114688      activation_220[0][0]             
__________________________________________________________________________________________________
conv2d_226 (Conv2D)             (None, 17, 17, 128)  114688      activation_225[0][0]             
__________________________________________________________________________________________________
batch_normalization_221 (BatchN (None, 17, 17, 128)  384         conv2d_221[0][0]                 
__________________________________________________________________________________________________
batch_normalization_226 (BatchN (None, 17, 17, 128)  384         conv2d_226[0][0]                 
__________________________________________________________________________________________________
activation_221 (Activation)     (None, 17, 17, 128)  0           batch_normalization_221[0][0]    
__________________________________________________________________________________________________
activation_226 (Activation)     (None, 17, 17, 128)  0           batch_normalization_226[0][0]    
__________________________________________________________________________________________________
average_pooling2d_22 (AveragePo (None, 17, 17, 768)  0           mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_219 (Conv2D)             (None, 17, 17, 192)  147456      mixed3[0][0]                     
__________________________________________________________________________________________________
conv2d_222 (Conv2D)             (None, 17, 17, 192)  172032      activation_221[0][0]             
__________________________________________________________________________________________________
conv2d_227 (Conv2D)             (None, 17, 17, 192)  172032      activation_226[0][0]             
__________________________________________________________________________________________________
conv2d_228 (Conv2D)             (None, 17, 17, 192)  147456      average_pooling2d_22[0][0]       
__________________________________________________________________________________________________
batch_normalization_219 (BatchN (None, 17, 17, 192)  576         conv2d_219[0][0]                 
__________________________________________________________________________________________________
batch_normalization_222 (BatchN (None, 17, 17, 192)  576         conv2d_222[0][0]                 
__________________________________________________________________________________________________
batch_normalization_227 (BatchN (None, 17, 17, 192)  576         conv2d_227[0][0]                 
__________________________________________________________________________________________________
batch_normalization_228 (BatchN (None, 17, 17, 192)  576         conv2d_228[0][0]                 
__________________________________________________________________________________________________
activation_219 (Activation)     (None, 17, 17, 192)  0           batch_normalization_219[0][0]    
__________________________________________________________________________________________________
activation_222 (Activation)     (None, 17, 17, 192)  0           batch_normalization_222[0][0]    
__________________________________________________________________________________________________
activation_227 (Activation)     (None, 17, 17, 192)  0           batch_normalization_227[0][0]    
__________________________________________________________________________________________________
activation_228 (Activation)     (None, 17, 17, 192)  0           batch_normalization_228[0][0]    
__________________________________________________________________________________________________
mixed4 (Concatenate)            (None, 17, 17, 768)  0           activation_219[0][0]             
                                                                 activation_222[0][0]             
                                                                 activation_227[0][0]             
                                                                 activation_228[0][0]             
__________________________________________________________________________________________________
conv2d_233 (Conv2D)             (None, 17, 17, 160)  122880      mixed4[0][0]                     
__________________________________________________________________________________________________
batch_normalization_233 (BatchN (None, 17, 17, 160)  480         conv2d_233[0][0]                 
__________________________________________________________________________________________________
activation_233 (Activation)     (None, 17, 17, 160)  0           batch_normalization_233[0][0]    
__________________________________________________________________________________________________
conv2d_234 (Conv2D)             (None, 17, 17, 160)  179200      activation_233[0][0]             
__________________________________________________________________________________________________
batch_normalization_234 (BatchN (None, 17, 17, 160)  480         conv2d_234[0][0]                 
__________________________________________________________________________________________________
activation_234 (Activation)     (None, 17, 17, 160)  0           batch_normalization_234[0][0]    
__________________________________________________________________________________________________
conv2d_230 (Conv2D)             (None, 17, 17, 160)  122880      mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_235 (Conv2D)             (None, 17, 17, 160)  179200      activation_234[0][0]             
__________________________________________________________________________________________________
batch_normalization_230 (BatchN (None, 17, 17, 160)  480         conv2d_230[0][0]                 
__________________________________________________________________________________________________
batch_normalization_235 (BatchN (None, 17, 17, 160)  480         conv2d_235[0][0]                 
__________________________________________________________________________________________________
activation_230 (Activation)     (None, 17, 17, 160)  0           batch_normalization_230[0][0]    
__________________________________________________________________________________________________
activation_235 (Activation)     (None, 17, 17, 160)  0           batch_normalization_235[0][0]    
__________________________________________________________________________________________________
conv2d_231 (Conv2D)             (None, 17, 17, 160)  179200      activation_230[0][0]             
__________________________________________________________________________________________________
conv2d_236 (Conv2D)             (None, 17, 17, 160)  179200      activation_235[0][0]             
__________________________________________________________________________________________________
batch_normalization_231 (BatchN (None, 17, 17, 160)  480         conv2d_231[0][0]                 
__________________________________________________________________________________________________
batch_normalization_236 (BatchN (None, 17, 17, 160)  480         conv2d_236[0][0]                 
__________________________________________________________________________________________________
activation_231 (Activation)     (None, 17, 17, 160)  0           batch_normalization_231[0][0]    
__________________________________________________________________________________________________
activation_236 (Activation)     (None, 17, 17, 160)  0           batch_normalization_236[0][0]    
__________________________________________________________________________________________________
average_pooling2d_23 (AveragePo (None, 17, 17, 768)  0           mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_229 (Conv2D)             (None, 17, 17, 192)  147456      mixed4[0][0]                     
__________________________________________________________________________________________________
conv2d_232 (Conv2D)             (None, 17, 17, 192)  215040      activation_231[0][0]             
__________________________________________________________________________________________________
conv2d_237 (Conv2D)             (None, 17, 17, 192)  215040      activation_236[0][0]             
__________________________________________________________________________________________________
conv2d_238 (Conv2D)             (None, 17, 17, 192)  147456      average_pooling2d_23[0][0]       
__________________________________________________________________________________________________
batch_normalization_229 (BatchN (None, 17, 17, 192)  576         conv2d_229[0][0]                 
__________________________________________________________________________________________________
batch_normalization_232 (BatchN (None, 17, 17, 192)  576         conv2d_232[0][0]                 
__________________________________________________________________________________________________
batch_normalization_237 (BatchN (None, 17, 17, 192)  576         conv2d_237[0][0]                 
__________________________________________________________________________________________________
batch_normalization_238 (BatchN (None, 17, 17, 192)  576         conv2d_238[0][0]                 
__________________________________________________________________________________________________
activation_229 (Activation)     (None, 17, 17, 192)  0           batch_normalization_229[0][0]    
__________________________________________________________________________________________________
activation_232 (Activation)     (None, 17, 17, 192)  0           batch_normalization_232[0][0]    
__________________________________________________________________________________________________
activation_237 (Activation)     (None, 17, 17, 192)  0           batch_normalization_237[0][0]    
__________________________________________________________________________________________________
activation_238 (Activation)     (None, 17, 17, 192)  0           batch_normalization_238[0][0]    
__________________________________________________________________________________________________
mixed5 (Concatenate)            (None, 17, 17, 768)  0           activation_229[0][0]             
                                                                 activation_232[0][0]             
                                                                 activation_237[0][0]             
                                                                 activation_238[0][0]             
__________________________________________________________________________________________________
conv2d_243 (Conv2D)             (None, 17, 17, 160)  122880      mixed5[0][0]                     
__________________________________________________________________________________________________
batch_normalization_243 (BatchN (None, 17, 17, 160)  480         conv2d_243[0][0]                 
__________________________________________________________________________________________________
activation_243 (Activation)     (None, 17, 17, 160)  0           batch_normalization_243[0][0]    
__________________________________________________________________________________________________
conv2d_244 (Conv2D)             (None, 17, 17, 160)  179200      activation_243[0][0]             
__________________________________________________________________________________________________
batch_normalization_244 (BatchN (None, 17, 17, 160)  480         conv2d_244[0][0]                 
__________________________________________________________________________________________________
activation_244 (Activation)     (None, 17, 17, 160)  0           batch_normalization_244[0][0]    
__________________________________________________________________________________________________
conv2d_240 (Conv2D)             (None, 17, 17, 160)  122880      mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_245 (Conv2D)             (None, 17, 17, 160)  179200      activation_244[0][0]             
__________________________________________________________________________________________________
batch_normalization_240 (BatchN (None, 17, 17, 160)  480         conv2d_240[0][0]                 
__________________________________________________________________________________________________
batch_normalization_245 (BatchN (None, 17, 17, 160)  480         conv2d_245[0][0]                 
__________________________________________________________________________________________________
activation_240 (Activation)     (None, 17, 17, 160)  0           batch_normalization_240[0][0]    
__________________________________________________________________________________________________
activation_245 (Activation)     (None, 17, 17, 160)  0           batch_normalization_245[0][0]    
__________________________________________________________________________________________________
conv2d_241 (Conv2D)             (None, 17, 17, 160)  179200      activation_240[0][0]             
__________________________________________________________________________________________________
conv2d_246 (Conv2D)             (None, 17, 17, 160)  179200      activation_245[0][0]             
__________________________________________________________________________________________________
batch_normalization_241 (BatchN (None, 17, 17, 160)  480         conv2d_241[0][0]                 
__________________________________________________________________________________________________
batch_normalization_246 (BatchN (None, 17, 17, 160)  480         conv2d_246[0][0]                 
__________________________________________________________________________________________________
activation_241 (Activation)     (None, 17, 17, 160)  0           batch_normalization_241[0][0]    
__________________________________________________________________________________________________
activation_246 (Activation)     (None, 17, 17, 160)  0           batch_normalization_246[0][0]    
__________________________________________________________________________________________________
average_pooling2d_24 (AveragePo (None, 17, 17, 768)  0           mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_239 (Conv2D)             (None, 17, 17, 192)  147456      mixed5[0][0]                     
__________________________________________________________________________________________________
conv2d_242 (Conv2D)             (None, 17, 17, 192)  215040      activation_241[0][0]             
__________________________________________________________________________________________________
conv2d_247 (Conv2D)             (None, 17, 17, 192)  215040      activation_246[0][0]             
__________________________________________________________________________________________________
conv2d_248 (Conv2D)             (None, 17, 17, 192)  147456      average_pooling2d_24[0][0]       
__________________________________________________________________________________________________
batch_normalization_239 (BatchN (None, 17, 17, 192)  576         conv2d_239[0][0]                 
__________________________________________________________________________________________________
batch_normalization_242 (BatchN (None, 17, 17, 192)  576         conv2d_242[0][0]                 
__________________________________________________________________________________________________
batch_normalization_247 (BatchN (None, 17, 17, 192)  576         conv2d_247[0][0]                 
__________________________________________________________________________________________________
batch_normalization_248 (BatchN (None, 17, 17, 192)  576         conv2d_248[0][0]                 
__________________________________________________________________________________________________
activation_239 (Activation)     (None, 17, 17, 192)  0           batch_normalization_239[0][0]    
__________________________________________________________________________________________________
activation_242 (Activation)     (None, 17, 17, 192)  0           batch_normalization_242[0][0]    
__________________________________________________________________________________________________
activation_247 (Activation)     (None, 17, 17, 192)  0           batch_normalization_247[0][0]    
__________________________________________________________________________________________________
activation_248 (Activation)     (None, 17, 17, 192)  0           batch_normalization_248[0][0]    
__________________________________________________________________________________________________
mixed6 (Concatenate)            (None, 17, 17, 768)  0           activation_239[0][0]             
                                                                 activation_242[0][0]             
                                                                 activation_247[0][0]             
                                                                 activation_248[0][0]             
__________________________________________________________________________________________________
conv2d_253 (Conv2D)             (None, 17, 17, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
batch_normalization_253 (BatchN (None, 17, 17, 192)  576         conv2d_253[0][0]                 
__________________________________________________________________________________________________
activation_253 (Activation)     (None, 17, 17, 192)  0           batch_normalization_253[0][0]    
__________________________________________________________________________________________________
conv2d_254 (Conv2D)             (None, 17, 17, 192)  258048      activation_253[0][0]             
__________________________________________________________________________________________________
batch_normalization_254 (BatchN (None, 17, 17, 192)  576         conv2d_254[0][0]                 
__________________________________________________________________________________________________
activation_254 (Activation)     (None, 17, 17, 192)  0           batch_normalization_254[0][0]    
__________________________________________________________________________________________________
conv2d_250 (Conv2D)             (None, 17, 17, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_255 (Conv2D)             (None, 17, 17, 192)  258048      activation_254[0][0]             
__________________________________________________________________________________________________
batch_normalization_250 (BatchN (None, 17, 17, 192)  576         conv2d_250[0][0]                 
__________________________________________________________________________________________________
batch_normalization_255 (BatchN (None, 17, 17, 192)  576         conv2d_255[0][0]                 
__________________________________________________________________________________________________
activation_250 (Activation)     (None, 17, 17, 192)  0           batch_normalization_250[0][0]    
__________________________________________________________________________________________________
activation_255 (Activation)     (None, 17, 17, 192)  0           batch_normalization_255[0][0]    
__________________________________________________________________________________________________
conv2d_251 (Conv2D)             (None, 17, 17, 192)  258048      activation_250[0][0]             
__________________________________________________________________________________________________
conv2d_256 (Conv2D)             (None, 17, 17, 192)  258048      activation_255[0][0]             
__________________________________________________________________________________________________
batch_normalization_251 (BatchN (None, 17, 17, 192)  576         conv2d_251[0][0]                 
__________________________________________________________________________________________________
batch_normalization_256 (BatchN (None, 17, 17, 192)  576         conv2d_256[0][0]                 
__________________________________________________________________________________________________
activation_251 (Activation)     (None, 17, 17, 192)  0           batch_normalization_251[0][0]    
__________________________________________________________________________________________________
activation_256 (Activation)     (None, 17, 17, 192)  0           batch_normalization_256[0][0]    
__________________________________________________________________________________________________
average_pooling2d_25 (AveragePo (None, 17, 17, 768)  0           mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_249 (Conv2D)             (None, 17, 17, 192)  147456      mixed6[0][0]                     
__________________________________________________________________________________________________
conv2d_252 (Conv2D)             (None, 17, 17, 192)  258048      activation_251[0][0]             
__________________________________________________________________________________________________
conv2d_257 (Conv2D)             (None, 17, 17, 192)  258048      activation_256[0][0]             
__________________________________________________________________________________________________
conv2d_258 (Conv2D)             (None, 17, 17, 192)  147456      average_pooling2d_25[0][0]       
__________________________________________________________________________________________________
batch_normalization_249 (BatchN (None, 17, 17, 192)  576         conv2d_249[0][0]                 
__________________________________________________________________________________________________
batch_normalization_252 (BatchN (None, 17, 17, 192)  576         conv2d_252[0][0]                 
__________________________________________________________________________________________________
batch_normalization_257 (BatchN (None, 17, 17, 192)  576         conv2d_257[0][0]                 
__________________________________________________________________________________________________
batch_normalization_258 (BatchN (None, 17, 17, 192)  576         conv2d_258[0][0]                 
__________________________________________________________________________________________________
activation_249 (Activation)     (None, 17, 17, 192)  0           batch_normalization_249[0][0]    
__________________________________________________________________________________________________
activation_252 (Activation)     (None, 17, 17, 192)  0           batch_normalization_252[0][0]    
__________________________________________________________________________________________________
activation_257 (Activation)     (None, 17, 17, 192)  0           batch_normalization_257[0][0]    
__________________________________________________________________________________________________
activation_258 (Activation)     (None, 17, 17, 192)  0           batch_normalization_258[0][0]    
__________________________________________________________________________________________________
mixed7 (Concatenate)            (None, 17, 17, 768)  0           activation_249[0][0]             
                                                                 activation_252[0][0]             
                                                                 activation_257[0][0]             
                                                                 activation_258[0][0]             
__________________________________________________________________________________________________
conv2d_261 (Conv2D)             (None, 17, 17, 192)  147456      mixed7[0][0]                     
__________________________________________________________________________________________________
batch_normalization_261 (BatchN (None, 17, 17, 192)  576         conv2d_261[0][0]                 
__________________________________________________________________________________________________
activation_261 (Activation)     (None, 17, 17, 192)  0           batch_normalization_261[0][0]    
__________________________________________________________________________________________________
conv2d_262 (Conv2D)             (None, 17, 17, 192)  258048      activation_261[0][0]             
__________________________________________________________________________________________________
batch_normalization_262 (BatchN (None, 17, 17, 192)  576         conv2d_262[0][0]                 
__________________________________________________________________________________________________
activation_262 (Activation)     (None, 17, 17, 192)  0           batch_normalization_262[0][0]    
__________________________________________________________________________________________________
conv2d_259 (Conv2D)             (None, 17, 17, 192)  147456      mixed7[0][0]                     
__________________________________________________________________________________________________
conv2d_263 (Conv2D)             (None, 17, 17, 192)  258048      activation_262[0][0]             
__________________________________________________________________________________________________
batch_normalization_259 (BatchN (None, 17, 17, 192)  576         conv2d_259[0][0]                 
__________________________________________________________________________________________________
batch_normalization_263 (BatchN (None, 17, 17, 192)  576         conv2d_263[0][0]                 
__________________________________________________________________________________________________
activation_259 (Activation)     (None, 17, 17, 192)  0           batch_normalization_259[0][0]    
__________________________________________________________________________________________________
activation_263 (Activation)     (None, 17, 17, 192)  0           batch_normalization_263[0][0]    
__________________________________________________________________________________________________
conv2d_260 (Conv2D)             (None, 8, 8, 320)    552960      activation_259[0][0]             
__________________________________________________________________________________________________
conv2d_264 (Conv2D)             (None, 8, 8, 192)    331776      activation_263[0][0]             
__________________________________________________________________________________________________
batch_normalization_260 (BatchN (None, 8, 8, 320)    960         conv2d_260[0][0]                 
__________________________________________________________________________________________________
batch_normalization_264 (BatchN (None, 8, 8, 192)    576         conv2d_264[0][0]                 
__________________________________________________________________________________________________
activation_260 (Activation)     (None, 8, 8, 320)    0           batch_normalization_260[0][0]    
__________________________________________________________________________________________________
activation_264 (Activation)     (None, 8, 8, 192)    0           batch_normalization_264[0][0]    
__________________________________________________________________________________________________
max_pooling2d_12 (MaxPooling2D) (None, 8, 8, 768)    0           mixed7[0][0]                     
__________________________________________________________________________________________________
mixed8 (Concatenate)            (None, 8, 8, 1280)   0           activation_260[0][0]             
                                                                 activation_264[0][0]             
                                                                 max_pooling2d_12[0][0]           
__________________________________________________________________________________________________
conv2d_269 (Conv2D)             (None, 8, 8, 448)    573440      mixed8[0][0]                     
__________________________________________________________________________________________________
batch_normalization_269 (BatchN (None, 8, 8, 448)    1344        conv2d_269[0][0]                 
__________________________________________________________________________________________________
activation_269 (Activation)     (None, 8, 8, 448)    0           batch_normalization_269[0][0]    
__________________________________________________________________________________________________
conv2d_266 (Conv2D)             (None, 8, 8, 384)    491520      mixed8[0][0]                     
__________________________________________________________________________________________________
conv2d_270 (Conv2D)             (None, 8, 8, 384)    1548288     activation_269[0][0]             
__________________________________________________________________________________________________
batch_normalization_266 (BatchN (None, 8, 8, 384)    1152        conv2d_266[0][0]                 
__________________________________________________________________________________________________
batch_normalization_270 (BatchN (None, 8, 8, 384)    1152        conv2d_270[0][0]                 
__________________________________________________________________________________________________
activation_266 (Activation)     (None, 8, 8, 384)    0           batch_normalization_266[0][0]    
__________________________________________________________________________________________________
activation_270 (Activation)     (None, 8, 8, 384)    0           batch_normalization_270[0][0]    
__________________________________________________________________________________________________
conv2d_267 (Conv2D)             (None, 8, 8, 384)    442368      activation_266[0][0]             
__________________________________________________________________________________________________
conv2d_268 (Conv2D)             (None, 8, 8, 384)    442368      activation_266[0][0]             
__________________________________________________________________________________________________
conv2d_271 (Conv2D)             (None, 8, 8, 384)    442368      activation_270[0][0]             
__________________________________________________________________________________________________
conv2d_272 (Conv2D)             (None, 8, 8, 384)    442368      activation_270[0][0]             
__________________________________________________________________________________________________
average_pooling2d_26 (AveragePo (None, 8, 8, 1280)   0           mixed8[0][0]                     
__________________________________________________________________________________________________
conv2d_265 (Conv2D)             (None, 8, 8, 320)    409600      mixed8[0][0]                     
__________________________________________________________________________________________________
batch_normalization_267 (BatchN (None, 8, 8, 384)    1152        conv2d_267[0][0]                 
__________________________________________________________________________________________________
batch_normalization_268 (BatchN (None, 8, 8, 384)    1152        conv2d_268[0][0]                 
__________________________________________________________________________________________________
batch_normalization_271 (BatchN (None, 8, 8, 384)    1152        conv2d_271[0][0]                 
__________________________________________________________________________________________________
batch_normalization_272 (BatchN (None, 8, 8, 384)    1152        conv2d_272[0][0]                 
__________________________________________________________________________________________________
conv2d_273 (Conv2D)             (None, 8, 8, 192)    245760      average_pooling2d_26[0][0]       
__________________________________________________________________________________________________
batch_normalization_265 (BatchN (None, 8, 8, 320)    960         conv2d_265[0][0]                 
__________________________________________________________________________________________________
activation_267 (Activation)     (None, 8, 8, 384)    0           batch_normalization_267[0][0]    
__________________________________________________________________________________________________
activation_268 (Activation)     (None, 8, 8, 384)    0           batch_normalization_268[0][0]    
__________________________________________________________________________________________________
activation_271 (Activation)     (None, 8, 8, 384)    0           batch_normalization_271[0][0]    
__________________________________________________________________________________________________
activation_272 (Activation)     (None, 8, 8, 384)    0           batch_normalization_272[0][0]    
__________________________________________________________________________________________________
batch_normalization_273 (BatchN (None, 8, 8, 192)    576         conv2d_273[0][0]                 
__________________________________________________________________________________________________
activation_265 (Activation)     (None, 8, 8, 320)    0           batch_normalization_265[0][0]    
__________________________________________________________________________________________________
mixed9_0 (Concatenate)          (None, 8, 8, 768)    0           activation_267[0][0]             
                                                                 activation_268[0][0]             
__________________________________________________________________________________________________
concatenate_5 (Concatenate)     (None, 8, 8, 768)    0           activation_271[0][0]             
                                                                 activation_272[0][0]             
__________________________________________________________________________________________________
activation_273 (Activation)     (None, 8, 8, 192)    0           batch_normalization_273[0][0]    
__________________________________________________________________________________________________
mixed9 (Concatenate)            (None, 8, 8, 2048)   0           activation_265[0][0]             
                                                                 mixed9_0[0][0]                   
                                                                 concatenate_5[0][0]              
                                                                 activation_273[0][0]             
__________________________________________________________________________________________________
conv2d_278 (Conv2D)             (None, 8, 8, 448)    917504      mixed9[0][0]                     
__________________________________________________________________________________________________
batch_normalization_278 (BatchN (None, 8, 8, 448)    1344        conv2d_278[0][0]                 
__________________________________________________________________________________________________
activation_278 (Activation)     (None, 8, 8, 448)    0           batch_normalization_278[0][0]    
__________________________________________________________________________________________________
conv2d_275 (Conv2D)             (None, 8, 8, 384)    786432      mixed9[0][0]                     
__________________________________________________________________________________________________
conv2d_279 (Conv2D)             (None, 8, 8, 384)    1548288     activation_278[0][0]             
__________________________________________________________________________________________________
batch_normalization_275 (BatchN (None, 8, 8, 384)    1152        conv2d_275[0][0]                 
__________________________________________________________________________________________________
batch_normalization_279 (BatchN (None, 8, 8, 384)    1152        conv2d_279[0][0]                 
__________________________________________________________________________________________________
activation_275 (Activation)     (None, 8, 8, 384)    0           batch_normalization_275[0][0]    
__________________________________________________________________________________________________
activation_279 (Activation)     (None, 8, 8, 384)    0           batch_normalization_279[0][0]    
__________________________________________________________________________________________________
conv2d_276 (Conv2D)             (None, 8, 8, 384)    442368      activation_275[0][0]             
__________________________________________________________________________________________________
conv2d_277 (Conv2D)             (None, 8, 8, 384)    442368      activation_275[0][0]             
__________________________________________________________________________________________________
conv2d_280 (Conv2D)             (None, 8, 8, 384)    442368      activation_279[0][0]             
__________________________________________________________________________________________________
conv2d_281 (Conv2D)             (None, 8, 8, 384)    442368      activation_279[0][0]             
__________________________________________________________________________________________________
average_pooling2d_27 (AveragePo (None, 8, 8, 2048)   0           mixed9[0][0]                     
__________________________________________________________________________________________________
conv2d_274 (Conv2D)             (None, 8, 8, 320)    655360      mixed9[0][0]                     
__________________________________________________________________________________________________
batch_normalization_276 (BatchN (None, 8, 8, 384)    1152        conv2d_276[0][0]                 
__________________________________________________________________________________________________
batch_normalization_277 (BatchN (None, 8, 8, 384)    1152        conv2d_277[0][0]                 
__________________________________________________________________________________________________
batch_normalization_280 (BatchN (None, 8, 8, 384)    1152        conv2d_280[0][0]                 
__________________________________________________________________________________________________
batch_normalization_281 (BatchN (None, 8, 8, 384)    1152        conv2d_281[0][0]                 
__________________________________________________________________________________________________
conv2d_282 (Conv2D)             (None, 8, 8, 192)    393216      average_pooling2d_27[0][0]       
__________________________________________________________________________________________________
batch_normalization_274 (BatchN (None, 8, 8, 320)    960         conv2d_274[0][0]                 
__________________________________________________________________________________________________
activation_276 (Activation)     (None, 8, 8, 384)    0           batch_normalization_276[0][0]    
__________________________________________________________________________________________________
activation_277 (Activation)     (None, 8, 8, 384)    0           batch_normalization_277[0][0]    
__________________________________________________________________________________________________
activation_280 (Activation)     (None, 8, 8, 384)    0           batch_normalization_280[0][0]    
__________________________________________________________________________________________________
activation_281 (Activation)     (None, 8, 8, 384)    0           batch_normalization_281[0][0]    
__________________________________________________________________________________________________
batch_normalization_282 (BatchN (None, 8, 8, 192)    576         conv2d_282[0][0]                 
__________________________________________________________________________________________________
activation_274 (Activation)     (None, 8, 8, 320)    0           batch_normalization_274[0][0]    
__________________________________________________________________________________________________
mixed9_1 (Concatenate)          (None, 8, 8, 768)    0           activation_276[0][0]             
                                                                 activation_277[0][0]             
__________________________________________________________________________________________________
concatenate_6 (Concatenate)     (None, 8, 8, 768)    0           activation_280[0][0]             
                                                                 activation_281[0][0]             
__________________________________________________________________________________________________
activation_282 (Activation)     (None, 8, 8, 192)    0           batch_normalization_282[0][0]    
__________________________________________________________________________________________________
mixed10 (Concatenate)           (None, 8, 8, 2048)   0           activation_274[0][0]             
                                                                 mixed9_1[0][0]                   
                                                                 concatenate_6[0][0]              
                                                                 activation_282[0][0]             
__________________________________________________________________________________________________
global_average_pooling2d_3 (Glo (None, 2048)         0           mixed10[0][0]                    
__________________________________________________________________________________________________
dropout_3 (Dropout)             (None, 2048)         0           global_average_pooling2d_3[0][0] 
__________________________________________________________________________________________________
dense_3 (Dense)                 (None, 1)            2049        dropout_3[0][0]                  
==================================================================================================
Total params: 21,804,833
Trainable params: 2,049
Non-trainable params: 21,802,784
__________________________________________________________________________________________________

earlystop = EarlyStopping(monitor='val_loss', patience=5, verbose=0, mode='auto')

model_InceptionV3.compile(loss = 'binary_crossentropy', optimizer = 'Adam', metrics =['accuracy'])
model_InceptionV3_history = model_InceptionV3.fit_generator(train_generator(X_train, y_train, batch_size=batch_size),
                                                    steps_per_epoch=len(y_train)//batch_size, epochs=epochs,
                                                    validation_data = val_generator(X_val, y_val, batch_size=batch_size),
                                                    validation_steps=len(y_val)//batch_size,
                                                    callbacks = [earlystop],
                                                    verbose=2)

Epoch 1/10
 - 240s - loss: 0.2065 - acc: 0.9227 - val_loss: 0.0825 - val_acc: 0.9724
Epoch 2/10
 - 240s - loss: 0.1164 - acc: 0.9567 - val_loss: 0.0743 - val_acc: 0.9754
Epoch 3/10
 - 240s - loss: 0.1058 - acc: 0.9597 - val_loss: 0.0787 - val_acc: 0.9742
Epoch 4/10
 - 240s - loss: 0.1031 - acc: 0.9617 - val_loss: 0.0782 - val_acc: 0.9760
Epoch 5/10
 - 240s - loss: 0.0967 - acc: 0.9637 - val_loss: 0.0736 - val_acc: 0.9778
Epoch 6/10
 - 240s - loss: 0.0939 - acc: 0.9636 - val_loss: 0.0654 - val_acc: 0.9810
Epoch 7/10
 - 240s - loss: 0.0945 - acc: 0.9646 - val_loss: 0.0840 - val_acc: 0.9744
Epoch 8/10
 - 240s - loss: 0.0938 - acc: 0.9648 - val_loss: 0.0822 - val_acc: 0.9756
Epoch 9/10
 - 240s - loss: 0.0914 - acc: 0.9663 - val_loss: 0.0721 - val_acc: 0.9788
Epoch 10/10
 - 240s - loss: 0.0912 - acc: 0.9648 - val_loss: 0.0848 - val_acc: 0.9752

from matplotlib import pyplot as plt  
history=model_InceptionV3_history  
# summarize history for accuracy
plt.plot(history.history['acc'])  
plt.plot(history.history['val_acc'])
plt.title('model accuracy')  
plt.ylabel('accuracy')  
plt.xlabel('epoch')  
plt.grid()
plt.legend(['train', 'test'], loc='lower right')  
plt.show()  
# summarize history for loss  
plt.plot(history.history['loss'])  
plt.plot(history.history['val_loss'])  
plt.title('model loss')  
plt.ylabel('loss')  
plt.xlabel('epoch')  
plt.grid()
plt.legend(['train', 'test'], loc='upper right')  
plt.show()  

# define train_generator function, yield batchs of train and validation data 
def train_gen_224(X, y, batch_size): 
    
    datalen = len(y)
    counter = datalen//batch_size
    while (True):
        
        for i in range(counter):
            X_224 = np.zeros((batch_size,224,224,3),dtype = np.float)
            for j in range(batch_size):
                X_224[j] = cv2.resize(cv2.imread(X[i* batch_size+j]),(224,224))
                
            X_224 = resnet_input(X_224)
            yield X_224, y[i * batch_size:(i + 1) * batch_size]

def val_gen_224(X, y, batch_size):
    
    datalen = len(y)
    counter = datalen//batch_size
    while (True):
        
        for i in range(counter):
            X_224 = np.zeros((batch_size,224,224,3),dtype = np.float)
            for j in range(batch_size):
                X_224[j] = cv2.resize(cv2.imread(X[i* batch_size+j]),(224,224))
                
            X_224 = resnet_input(X_224)
            yield X_224, y[i * batch_size:(i + 1) * batch_size]

base_model = ResNet50(include_top=False, weights='imagenet', input_shape=(224,224,3),pooling='avg')
for layer in base_model.layers:
    layer.trainable = False
x = Dropout(0.5)(base_model.output)
x = Dense(1, activation='sigmoid')(x)
model_ResNet50 = Model(inputs = base_model.input, outputs=x, name = 'model_ResNet50')
model_ResNet50.summary()

__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_4 (InputLayer)            (None, 224, 224, 3)  0                                            
__________________________________________________________________________________________________
conv1_pad (ZeroPadding2D)       (None, 230, 230, 3)  0           input_4[0][0]                    
__________________________________________________________________________________________________
conv1 (Conv2D)                  (None, 112, 112, 64) 9472        conv1_pad[0][0]                  
__________________________________________________________________________________________________
bn_conv1 (BatchNormalization)   (None, 112, 112, 64) 256         conv1[0][0]                      
__________________________________________________________________________________________________
activation_283 (Activation)     (None, 112, 112, 64) 0           bn_conv1[0][0]                   
__________________________________________________________________________________________________
max_pooling2d_13 (MaxPooling2D) (None, 55, 55, 64)   0           activation_283[0][0]             
__________________________________________________________________________________________________
res2a_branch2a (Conv2D)         (None, 55, 55, 64)   4160        max_pooling2d_13[0][0]           
__________________________________________________________________________________________________
bn2a_branch2a (BatchNormalizati (None, 55, 55, 64)   256         res2a_branch2a[0][0]             
__________________________________________________________________________________________________
activation_284 (Activation)     (None, 55, 55, 64)   0           bn2a_branch2a[0][0]              
__________________________________________________________________________________________________
res2a_branch2b (Conv2D)         (None, 55, 55, 64)   36928       activation_284[0][0]             
__________________________________________________________________________________________________
bn2a_branch2b (BatchNormalizati (None, 55, 55, 64)   256         res2a_branch2b[0][0]             
__________________________________________________________________________________________________
activation_285 (Activation)     (None, 55, 55, 64)   0           bn2a_branch2b[0][0]              
__________________________________________________________________________________________________
res2a_branch2c (Conv2D)         (None, 55, 55, 256)  16640       activation_285[0][0]             
__________________________________________________________________________________________________
res2a_branch1 (Conv2D)          (None, 55, 55, 256)  16640       max_pooling2d_13[0][0]           
__________________________________________________________________________________________________
bn2a_branch2c (BatchNormalizati (None, 55, 55, 256)  1024        res2a_branch2c[0][0]             
__________________________________________________________________________________________________
bn2a_branch1 (BatchNormalizatio (None, 55, 55, 256)  1024        res2a_branch1[0][0]              
__________________________________________________________________________________________________
add_1 (Add)                     (None, 55, 55, 256)  0           bn2a_branch2c[0][0]              
                                                                 bn2a_branch1[0][0]               
__________________________________________________________________________________________________
activation_286 (Activation)     (None, 55, 55, 256)  0           add_1[0][0]                      
__________________________________________________________________________________________________
res2b_branch2a (Conv2D)         (None, 55, 55, 64)   16448       activation_286[0][0]             
__________________________________________________________________________________________________
bn2b_branch2a (BatchNormalizati (None, 55, 55, 64)   256         res2b_branch2a[0][0]             
__________________________________________________________________________________________________
activation_287 (Activation)     (None, 55, 55, 64)   0           bn2b_branch2a[0][0]              
__________________________________________________________________________________________________
res2b_branch2b (Conv2D)         (None, 55, 55, 64)   36928       activation_287[0][0]             
__________________________________________________________________________________________________
bn2b_branch2b (BatchNormalizati (None, 55, 55, 64)   256         res2b_branch2b[0][0]             
__________________________________________________________________________________________________
activation_288 (Activation)     (None, 55, 55, 64)   0           bn2b_branch2b[0][0]              
__________________________________________________________________________________________________
res2b_branch2c (Conv2D)         (None, 55, 55, 256)  16640       activation_288[0][0]             
__________________________________________________________________________________________________
bn2b_branch2c (BatchNormalizati (None, 55, 55, 256)  1024        res2b_branch2c[0][0]             
__________________________________________________________________________________________________
add_2 (Add)                     (None, 55, 55, 256)  0           bn2b_branch2c[0][0]              
                                                                 activation_286[0][0]             
__________________________________________________________________________________________________
activation_289 (Activation)     (None, 55, 55, 256)  0           add_2[0][0]                      
__________________________________________________________________________________________________
res2c_branch2a (Conv2D)         (None, 55, 55, 64)   16448       activation_289[0][0]             
__________________________________________________________________________________________________
bn2c_branch2a (BatchNormalizati (None, 55, 55, 64)   256         res2c_branch2a[0][0]             
__________________________________________________________________________________________________
activation_290 (Activation)     (None, 55, 55, 64)   0           bn2c_branch2a[0][0]              
__________________________________________________________________________________________________
res2c_branch2b (Conv2D)         (None, 55, 55, 64)   36928       activation_290[0][0]             
__________________________________________________________________________________________________
bn2c_branch2b (BatchNormalizati (None, 55, 55, 64)   256         res2c_branch2b[0][0]             
__________________________________________________________________________________________________
activation_291 (Activation)     (None, 55, 55, 64)   0           bn2c_branch2b[0][0]              
__________________________________________________________________________________________________
res2c_branch2c (Conv2D)         (None, 55, 55, 256)  16640       activation_291[0][0]             
__________________________________________________________________________________________________
bn2c_branch2c (BatchNormalizati (None, 55, 55, 256)  1024        res2c_branch2c[0][0]             
__________________________________________________________________________________________________
add_3 (Add)                     (None, 55, 55, 256)  0           bn2c_branch2c[0][0]              
                                                                 activation_289[0][0]             
__________________________________________________________________________________________________
activation_292 (Activation)     (None, 55, 55, 256)  0           add_3[0][0]                      
__________________________________________________________________________________________________
res3a_branch2a (Conv2D)         (None, 28, 28, 128)  32896       activation_292[0][0]             
__________________________________________________________________________________________________
bn3a_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3a_branch2a[0][0]             
__________________________________________________________________________________________________
activation_293 (Activation)     (None, 28, 28, 128)  0           bn3a_branch2a[0][0]              
__________________________________________________________________________________________________
res3a_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_293[0][0]             
__________________________________________________________________________________________________
bn3a_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3a_branch2b[0][0]             
__________________________________________________________________________________________________
activation_294 (Activation)     (None, 28, 28, 128)  0           bn3a_branch2b[0][0]              
__________________________________________________________________________________________________
res3a_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_294[0][0]             
__________________________________________________________________________________________________
res3a_branch1 (Conv2D)          (None, 28, 28, 512)  131584      activation_292[0][0]             
__________________________________________________________________________________________________
bn3a_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3a_branch2c[0][0]             
__________________________________________________________________________________________________
bn3a_branch1 (BatchNormalizatio (None, 28, 28, 512)  2048        res3a_branch1[0][0]              
__________________________________________________________________________________________________
add_4 (Add)                     (None, 28, 28, 512)  0           bn3a_branch2c[0][0]              
                                                                 bn3a_branch1[0][0]               
__________________________________________________________________________________________________
activation_295 (Activation)     (None, 28, 28, 512)  0           add_4[0][0]                      
__________________________________________________________________________________________________
res3b_branch2a (Conv2D)         (None, 28, 28, 128)  65664       activation_295[0][0]             
__________________________________________________________________________________________________
bn3b_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3b_branch2a[0][0]             
__________________________________________________________________________________________________
activation_296 (Activation)     (None, 28, 28, 128)  0           bn3b_branch2a[0][0]              
__________________________________________________________________________________________________
res3b_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_296[0][0]             
__________________________________________________________________________________________________
bn3b_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3b_branch2b[0][0]             
__________________________________________________________________________________________________
activation_297 (Activation)     (None, 28, 28, 128)  0           bn3b_branch2b[0][0]              
__________________________________________________________________________________________________
res3b_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_297[0][0]             
__________________________________________________________________________________________________
bn3b_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3b_branch2c[0][0]             
__________________________________________________________________________________________________
add_5 (Add)                     (None, 28, 28, 512)  0           bn3b_branch2c[0][0]              
                                                                 activation_295[0][0]             
__________________________________________________________________________________________________
activation_298 (Activation)     (None, 28, 28, 512)  0           add_5[0][0]                      
__________________________________________________________________________________________________
res3c_branch2a (Conv2D)         (None, 28, 28, 128)  65664       activation_298[0][0]             
__________________________________________________________________________________________________
bn3c_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3c_branch2a[0][0]             
__________________________________________________________________________________________________
activation_299 (Activation)     (None, 28, 28, 128)  0           bn3c_branch2a[0][0]              
__________________________________________________________________________________________________
res3c_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_299[0][0]             
__________________________________________________________________________________________________
bn3c_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3c_branch2b[0][0]             
__________________________________________________________________________________________________
activation_300 (Activation)     (None, 28, 28, 128)  0           bn3c_branch2b[0][0]              
__________________________________________________________________________________________________
res3c_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_300[0][0]             
__________________________________________________________________________________________________
bn3c_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3c_branch2c[0][0]             
__________________________________________________________________________________________________
add_6 (Add)                     (None, 28, 28, 512)  0           bn3c_branch2c[0][0]              
                                                                 activation_298[0][0]             
__________________________________________________________________________________________________
activation_301 (Activation)     (None, 28, 28, 512)  0           add_6[0][0]                      
__________________________________________________________________________________________________
res3d_branch2a (Conv2D)         (None, 28, 28, 128)  65664       activation_301[0][0]             
__________________________________________________________________________________________________
bn3d_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3d_branch2a[0][0]             
__________________________________________________________________________________________________
activation_302 (Activation)     (None, 28, 28, 128)  0           bn3d_branch2a[0][0]              
__________________________________________________________________________________________________
res3d_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_302[0][0]             
__________________________________________________________________________________________________
bn3d_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3d_branch2b[0][0]             
__________________________________________________________________________________________________
activation_303 (Activation)     (None, 28, 28, 128)  0           bn3d_branch2b[0][0]              
__________________________________________________________________________________________________
res3d_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_303[0][0]             
__________________________________________________________________________________________________
bn3d_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3d_branch2c[0][0]             
__________________________________________________________________________________________________
add_7 (Add)                     (None, 28, 28, 512)  0           bn3d_branch2c[0][0]              
                                                                 activation_301[0][0]             
__________________________________________________________________________________________________
activation_304 (Activation)     (None, 28, 28, 512)  0           add_7[0][0]                      
__________________________________________________________________________________________________
res4a_branch2a (Conv2D)         (None, 14, 14, 256)  131328      activation_304[0][0]             
__________________________________________________________________________________________________
bn4a_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4a_branch2a[0][0]             
__________________________________________________________________________________________________
activation_305 (Activation)     (None, 14, 14, 256)  0           bn4a_branch2a[0][0]              
__________________________________________________________________________________________________
res4a_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_305[0][0]             
__________________________________________________________________________________________________
bn4a_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4a_branch2b[0][0]             
__________________________________________________________________________________________________
activation_306 (Activation)     (None, 14, 14, 256)  0           bn4a_branch2b[0][0]              
__________________________________________________________________________________________________
res4a_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_306[0][0]             
__________________________________________________________________________________________________
res4a_branch1 (Conv2D)          (None, 14, 14, 1024) 525312      activation_304[0][0]             
__________________________________________________________________________________________________
bn4a_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4a_branch2c[0][0]             
__________________________________________________________________________________________________
bn4a_branch1 (BatchNormalizatio (None, 14, 14, 1024) 4096        res4a_branch1[0][0]              
__________________________________________________________________________________________________
add_8 (Add)                     (None, 14, 14, 1024) 0           bn4a_branch2c[0][0]              
                                                                 bn4a_branch1[0][0]               
__________________________________________________________________________________________________
activation_307 (Activation)     (None, 14, 14, 1024) 0           add_8[0][0]                      
__________________________________________________________________________________________________
res4b_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_307[0][0]             
__________________________________________________________________________________________________
bn4b_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4b_branch2a[0][0]             
__________________________________________________________________________________________________
activation_308 (Activation)     (None, 14, 14, 256)  0           bn4b_branch2a[0][0]              
__________________________________________________________________________________________________
res4b_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_308[0][0]             
__________________________________________________________________________________________________
bn4b_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4b_branch2b[0][0]             
__________________________________________________________________________________________________
activation_309 (Activation)     (None, 14, 14, 256)  0           bn4b_branch2b[0][0]              
__________________________________________________________________________________________________
res4b_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_309[0][0]             
__________________________________________________________________________________________________
bn4b_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4b_branch2c[0][0]             
__________________________________________________________________________________________________
add_9 (Add)                     (None, 14, 14, 1024) 0           bn4b_branch2c[0][0]              
                                                                 activation_307[0][0]             
__________________________________________________________________________________________________
activation_310 (Activation)     (None, 14, 14, 1024) 0           add_9[0][0]                      
__________________________________________________________________________________________________
res4c_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_310[0][0]             
__________________________________________________________________________________________________
bn4c_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4c_branch2a[0][0]             
__________________________________________________________________________________________________
activation_311 (Activation)     (None, 14, 14, 256)  0           bn4c_branch2a[0][0]              
__________________________________________________________________________________________________
res4c_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_311[0][0]             
__________________________________________________________________________________________________
bn4c_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4c_branch2b[0][0]             
__________________________________________________________________________________________________
activation_312 (Activation)     (None, 14, 14, 256)  0           bn4c_branch2b[0][0]              
__________________________________________________________________________________________________
res4c_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_312[0][0]             
__________________________________________________________________________________________________
bn4c_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4c_branch2c[0][0]             
__________________________________________________________________________________________________
add_10 (Add)                    (None, 14, 14, 1024) 0           bn4c_branch2c[0][0]              
                                                                 activation_310[0][0]             
__________________________________________________________________________________________________
activation_313 (Activation)     (None, 14, 14, 1024) 0           add_10[0][0]                     
__________________________________________________________________________________________________
res4d_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_313[0][0]             
__________________________________________________________________________________________________
bn4d_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4d_branch2a[0][0]             
__________________________________________________________________________________________________
activation_314 (Activation)     (None, 14, 14, 256)  0           bn4d_branch2a[0][0]              
__________________________________________________________________________________________________
res4d_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_314[0][0]             
__________________________________________________________________________________________________
bn4d_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4d_branch2b[0][0]             
__________________________________________________________________________________________________
activation_315 (Activation)     (None, 14, 14, 256)  0           bn4d_branch2b[0][0]              
__________________________________________________________________________________________________
res4d_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_315[0][0]             
__________________________________________________________________________________________________
bn4d_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4d_branch2c[0][0]             
__________________________________________________________________________________________________
add_11 (Add)                    (None, 14, 14, 1024) 0           bn4d_branch2c[0][0]              
                                                                 activation_313[0][0]             
__________________________________________________________________________________________________
activation_316 (Activation)     (None, 14, 14, 1024) 0           add_11[0][0]                     
__________________________________________________________________________________________________
res4e_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_316[0][0]             
__________________________________________________________________________________________________
bn4e_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4e_branch2a[0][0]             
__________________________________________________________________________________________________
activation_317 (Activation)     (None, 14, 14, 256)  0           bn4e_branch2a[0][0]              
__________________________________________________________________________________________________
res4e_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_317[0][0]             
__________________________________________________________________________________________________
bn4e_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4e_branch2b[0][0]             
__________________________________________________________________________________________________
activation_318 (Activation)     (None, 14, 14, 256)  0           bn4e_branch2b[0][0]              
__________________________________________________________________________________________________
res4e_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_318[0][0]             
__________________________________________________________________________________________________
bn4e_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4e_branch2c[0][0]             
__________________________________________________________________________________________________
add_12 (Add)                    (None, 14, 14, 1024) 0           bn4e_branch2c[0][0]              
                                                                 activation_316[0][0]             
__________________________________________________________________________________________________
activation_319 (Activation)     (None, 14, 14, 1024) 0           add_12[0][0]                     
__________________________________________________________________________________________________
res4f_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_319[0][0]             
__________________________________________________________________________________________________
bn4f_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4f_branch2a[0][0]             
__________________________________________________________________________________________________
activation_320 (Activation)     (None, 14, 14, 256)  0           bn4f_branch2a[0][0]              
__________________________________________________________________________________________________
res4f_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_320[0][0]             
__________________________________________________________________________________________________
bn4f_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4f_branch2b[0][0]             
__________________________________________________________________________________________________
activation_321 (Activation)     (None, 14, 14, 256)  0           bn4f_branch2b[0][0]              
__________________________________________________________________________________________________
res4f_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_321[0][0]             
__________________________________________________________________________________________________
bn4f_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4f_branch2c[0][0]             
__________________________________________________________________________________________________
add_13 (Add)                    (None, 14, 14, 1024) 0           bn4f_branch2c[0][0]              
                                                                 activation_319[0][0]             
__________________________________________________________________________________________________
activation_322 (Activation)     (None, 14, 14, 1024) 0           add_13[0][0]                     
__________________________________________________________________________________________________
res5a_branch2a (Conv2D)         (None, 7, 7, 512)    524800      activation_322[0][0]             
__________________________________________________________________________________________________
bn5a_branch2a (BatchNormalizati (None, 7, 7, 512)    2048        res5a_branch2a[0][0]             
__________________________________________________________________________________________________
activation_323 (Activation)     (None, 7, 7, 512)    0           bn5a_branch2a[0][0]              
__________________________________________________________________________________________________
res5a_branch2b (Conv2D)         (None, 7, 7, 512)    2359808     activation_323[0][0]             
__________________________________________________________________________________________________
bn5a_branch2b (BatchNormalizati (None, 7, 7, 512)    2048        res5a_branch2b[0][0]             
__________________________________________________________________________________________________
activation_324 (Activation)     (None, 7, 7, 512)    0           bn5a_branch2b[0][0]              
__________________________________________________________________________________________________
res5a_branch2c (Conv2D)         (None, 7, 7, 2048)   1050624     activation_324[0][0]             
__________________________________________________________________________________________________
res5a_branch1 (Conv2D)          (None, 7, 7, 2048)   2099200     activation_322[0][0]             
__________________________________________________________________________________________________
bn5a_branch2c (BatchNormalizati (None, 7, 7, 2048)   8192        res5a_branch2c[0][0]             
__________________________________________________________________________________________________
bn5a_branch1 (BatchNormalizatio (None, 7, 7, 2048)   8192        res5a_branch1[0][0]              
__________________________________________________________________________________________________
add_14 (Add)                    (None, 7, 7, 2048)   0           bn5a_branch2c[0][0]              
                                                                 bn5a_branch1[0][0]               
__________________________________________________________________________________________________
activation_325 (Activation)     (None, 7, 7, 2048)   0           add_14[0][0]                     
__________________________________________________________________________________________________
res5b_branch2a (Conv2D)         (None, 7, 7, 512)    1049088     activation_325[0][0]             
__________________________________________________________________________________________________
bn5b_branch2a (BatchNormalizati (None, 7, 7, 512)    2048        res5b_branch2a[0][0]             
__________________________________________________________________________________________________
activation_326 (Activation)     (None, 7, 7, 512)    0           bn5b_branch2a[0][0]              
__________________________________________________________________________________________________
res5b_branch2b (Conv2D)         (None, 7, 7, 512)    2359808     activation_326[0][0]             
__________________________________________________________________________________________________
bn5b_branch2b (BatchNormalizati (None, 7, 7, 512)    2048        res5b_branch2b[0][0]             
__________________________________________________________________________________________________
activation_327 (Activation)     (None, 7, 7, 512)    0           bn5b_branch2b[0][0]              
__________________________________________________________________________________________________
res5b_branch2c (Conv2D)         (None, 7, 7, 2048)   1050624     activation_327[0][0]             
__________________________________________________________________________________________________
bn5b_branch2c (BatchNormalizati (None, 7, 7, 2048)   8192        res5b_branch2c[0][0]             
__________________________________________________________________________________________________
add_15 (Add)                    (None, 7, 7, 2048)   0           bn5b_branch2c[0][0]              
                                                                 activation_325[0][0]             
__________________________________________________________________________________________________
activation_328 (Activation)     (None, 7, 7, 2048)   0           add_15[0][0]                     
__________________________________________________________________________________________________
res5c_branch2a (Conv2D)         (None, 7, 7, 512)    1049088     activation_328[0][0]             
__________________________________________________________________________________________________
bn5c_branch2a (BatchNormalizati (None, 7, 7, 512)    2048        res5c_branch2a[0][0]             
__________________________________________________________________________________________________
activation_329 (Activation)     (None, 7, 7, 512)    0           bn5c_branch2a[0][0]              
__________________________________________________________________________________________________
res5c_branch2b (Conv2D)         (None, 7, 7, 512)    2359808     activation_329[0][0]             
__________________________________________________________________________________________________
bn5c_branch2b (BatchNormalizati (None, 7, 7, 512)    2048        res5c_branch2b[0][0]             
__________________________________________________________________________________________________
activation_330 (Activation)     (None, 7, 7, 512)    0           bn5c_branch2b[0][0]              
__________________________________________________________________________________________________
res5c_branch2c (Conv2D)         (None, 7, 7, 2048)   1050624     activation_330[0][0]             
__________________________________________________________________________________________________
bn5c_branch2c (BatchNormalizati (None, 7, 7, 2048)   8192        res5c_branch2c[0][0]             
__________________________________________________________________________________________________
add_16 (Add)                    (None, 7, 7, 2048)   0           bn5c_branch2c[0][0]              
                                                                 activation_328[0][0]             
__________________________________________________________________________________________________
activation_331 (Activation)     (None, 7, 7, 2048)   0           add_16[0][0]                     
__________________________________________________________________________________________________
avg_pool (AveragePooling2D)     (None, 1, 1, 2048)   0           activation_331[0][0]             
__________________________________________________________________________________________________
global_average_pooling2d_4 (Glo (None, 2048)         0           avg_pool[0][0]                   
__________________________________________________________________________________________________
dropout_4 (Dropout)             (None, 2048)         0           global_average_pooling2d_4[0][0] 
__________________________________________________________________________________________________
dense_4 (Dense)                 (None, 1)            2049        dropout_4[0][0]                  
==================================================================================================
Total params: 23,589,761
Trainable params: 2,049
Non-trainable params: 23,587,712
__________________________________________________________________________________________________

earlystop = EarlyStopping(monitor='val_loss', patience=5, verbose=0, mode='auto')

model_ResNet50.compile(loss = 'binary_crossentropy', optimizer = 'Adam', metrics =['accuracy'])
model_ResNet50_history = model_ResNet50.fit_generator(train_gen_224(X_train, y_train, batch_size=batch_size),
                                                    steps_per_epoch=len(y_train)//batch_size, epochs=epochs,
                                                    validation_data = val_gen_224(X_val, y_val, batch_size=batch_size),
                                                    validation_steps=len(y_val)//batch_size,
                                                    callbacks = [earlystop],
                                                    verbose=2)

Epoch 1/10
 - 179s - loss: 0.1637 - acc: 0.9333 - val_loss: 0.0772 - val_acc: 0.9714
Epoch 2/10
 - 177s - loss: 0.0959 - acc: 0.9627 - val_loss: 0.0837 - val_acc: 0.9708
Epoch 3/10
 - 176s - loss: 0.0843 - acc: 0.9667 - val_loss: 0.0884 - val_acc: 0.9706
Epoch 4/10
 - 176s - loss: 0.0853 - acc: 0.9667 - val_loss: 0.0775 - val_acc: 0.9738
Epoch 5/10
 - 176s - loss: 0.0786 - acc: 0.9691 - val_loss: 0.0771 - val_acc: 0.9740
Epoch 6/10
 - 176s - loss: 0.0796 - acc: 0.9691 - val_loss: 0.0849 - val_acc: 0.9728
Epoch 7/10
 - 178s - loss: 0.0779 - acc: 0.9697 - val_loss: 0.0890 - val_acc: 0.9716
Epoch 8/10
 - 178s - loss: 0.0783 - acc: 0.9695 - val_loss: 0.1010 - val_acc: 0.9698
Epoch 9/10
 - 177s - loss: 0.0744 - acc: 0.9723 - val_loss: 0.0823 - val_acc: 0.9738
Epoch 10/10
 - 176s - loss: 0.0737 - acc: 0.9718 - val_loss: 0.0997 - val_acc: 0.9706

from matplotlib import pyplot as plt  
history=model_ResNet50_history  
# summarize history for accuracy
plt.plot(history.history['acc'])  
plt.plot(history.history['val_acc'])
plt.title('model accuracy')  
plt.ylabel('accuracy')  
plt.xlabel('epoch')  
plt.grid()
plt.legend(['train', 'test'], loc='lower right')  
plt.show()  
# summarize history for loss  
plt.plot(history.history['loss'])  
plt.plot(history.history['val_loss'])  
plt.title('model loss')  
plt.ylabel('loss')  
plt.xlabel('epoch')  
plt.grid()
plt.legend(['train', 'test'], loc='upper right')  
plt.show()  

base_model = Xception(include_top=False, weights='imagenet', input_shape=(299,299,3),pooling='avg')
for layer in base_model.layers:
    layer.trainable = False
x = Dropout(0.5)(base_model.output)
x = Dense(1, activation='sigmoid')(x)
model_Xception = Model(inputs = base_model.input, outputs=x, name = 'model_Xception')
model_Xception.summary()

__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_5 (InputLayer)            (None, 299, 299, 3)  0                                            
__________________________________________________________________________________________________
block1_conv1 (Conv2D)           (None, 149, 149, 32) 864         input_5[0][0]                    
__________________________________________________________________________________________________
block1_conv1_bn (BatchNormaliza (None, 149, 149, 32) 128         block1_conv1[0][0]               
__________________________________________________________________________________________________
block1_conv1_act (Activation)   (None, 149, 149, 32) 0           block1_conv1_bn[0][0]            
__________________________________________________________________________________________________
block1_conv2 (Conv2D)           (None, 147, 147, 64) 18432       block1_conv1_act[0][0]           
__________________________________________________________________________________________________
block1_conv2_bn (BatchNormaliza (None, 147, 147, 64) 256         block1_conv2[0][0]               
__________________________________________________________________________________________________
block1_conv2_act (Activation)   (None, 147, 147, 64) 0           block1_conv2_bn[0][0]            
__________________________________________________________________________________________________
block2_sepconv1 (SeparableConv2 (None, 147, 147, 128 8768        block1_conv2_act[0][0]           
__________________________________________________________________________________________________
block2_sepconv1_bn (BatchNormal (None, 147, 147, 128 512         block2_sepconv1[0][0]            
__________________________________________________________________________________________________
block2_sepconv2_act (Activation (None, 147, 147, 128 0           block2_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block2_sepconv2 (SeparableConv2 (None, 147, 147, 128 17536       block2_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block2_sepconv2_bn (BatchNormal (None, 147, 147, 128 512         block2_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_283 (Conv2D)             (None, 74, 74, 128)  8192        block1_conv2_act[0][0]           
__________________________________________________________________________________________________
block2_pool (MaxPooling2D)      (None, 74, 74, 128)  0           block2_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_283 (BatchN (None, 74, 74, 128)  512         conv2d_283[0][0]                 
__________________________________________________________________________________________________
add_17 (Add)                    (None, 74, 74, 128)  0           block2_pool[0][0]                
                                                                 batch_normalization_283[0][0]    
__________________________________________________________________________________________________
block3_sepconv1_act (Activation (None, 74, 74, 128)  0           add_17[0][0]                     
__________________________________________________________________________________________________
block3_sepconv1 (SeparableConv2 (None, 74, 74, 256)  33920       block3_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block3_sepconv1_bn (BatchNormal (None, 74, 74, 256)  1024        block3_sepconv1[0][0]            
__________________________________________________________________________________________________
block3_sepconv2_act (Activation (None, 74, 74, 256)  0           block3_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block3_sepconv2 (SeparableConv2 (None, 74, 74, 256)  67840       block3_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block3_sepconv2_bn (BatchNormal (None, 74, 74, 256)  1024        block3_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_284 (Conv2D)             (None, 37, 37, 256)  32768       add_17[0][0]                     
__________________________________________________________________________________________________
block3_pool (MaxPooling2D)      (None, 37, 37, 256)  0           block3_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_284 (BatchN (None, 37, 37, 256)  1024        conv2d_284[0][0]                 
__________________________________________________________________________________________________
add_18 (Add)                    (None, 37, 37, 256)  0           block3_pool[0][0]                
                                                                 batch_normalization_284[0][0]    
__________________________________________________________________________________________________
block4_sepconv1_act (Activation (None, 37, 37, 256)  0           add_18[0][0]                     
__________________________________________________________________________________________________
block4_sepconv1 (SeparableConv2 (None, 37, 37, 728)  188672      block4_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block4_sepconv1_bn (BatchNormal (None, 37, 37, 728)  2912        block4_sepconv1[0][0]            
__________________________________________________________________________________________________
block4_sepconv2_act (Activation (None, 37, 37, 728)  0           block4_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block4_sepconv2 (SeparableConv2 (None, 37, 37, 728)  536536      block4_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block4_sepconv2_bn (BatchNormal (None, 37, 37, 728)  2912        block4_sepconv2[0][0]            
__________________________________________________________________________________________________
conv2d_285 (Conv2D)             (None, 19, 19, 728)  186368      add_18[0][0]                     
__________________________________________________________________________________________________
block4_pool (MaxPooling2D)      (None, 19, 19, 728)  0           block4_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
batch_normalization_285 (BatchN (None, 19, 19, 728)  2912        conv2d_285[0][0]                 
__________________________________________________________________________________________________
add_19 (Add)                    (None, 19, 19, 728)  0           block4_pool[0][0]                
                                                                 batch_normalization_285[0][0]    
__________________________________________________________________________________________________
block5_sepconv1_act (Activation (None, 19, 19, 728)  0           add_19[0][0]                     
__________________________________________________________________________________________________
block5_sepconv1 (SeparableConv2 (None, 19, 19, 728)  536536      block5_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv1_bn (BatchNormal (None, 19, 19, 728)  2912        block5_sepconv1[0][0]            
__________________________________________________________________________________________________
block5_sepconv2_act (Activation (None, 19, 19, 728)  0           block5_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block5_sepconv2 (SeparableConv2 (None, 19, 19, 728)  536536      block5_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv2_bn (BatchNormal (None, 19, 19, 728)  2912        block5_sepconv2[0][0]            
__________________________________________________________________________________________________
block5_sepconv3_act (Activation (None, 19, 19, 728)  0           block5_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block5_sepconv3 (SeparableConv2 (None, 19, 19, 728)  536536      block5_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block5_sepconv3_bn (BatchNormal (None, 19, 19, 728)  2912        block5_sepconv3[0][0]            
__________________________________________________________________________________________________
add_20 (Add)                    (None, 19, 19, 728)  0           block5_sepconv3_bn[0][0]         
                                                                 add_19[0][0]                     
__________________________________________________________________________________________________
block6_sepconv1_act (Activation (None, 19, 19, 728)  0           add_20[0][0]                     
__________________________________________________________________________________________________
block6_sepconv1 (SeparableConv2 (None, 19, 19, 728)  536536      block6_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv1_bn (BatchNormal (None, 19, 19, 728)  2912        block6_sepconv1[0][0]            
__________________________________________________________________________________________________
block6_sepconv2_act (Activation (None, 19, 19, 728)  0           block6_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block6_sepconv2 (SeparableConv2 (None, 19, 19, 728)  536536      block6_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv2_bn (BatchNormal (None, 19, 19, 728)  2912        block6_sepconv2[0][0]            
__________________________________________________________________________________________________
block6_sepconv3_act (Activation (None, 19, 19, 728)  0           block6_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block6_sepconv3 (SeparableConv2 (None, 19, 19, 728)  536536      block6_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block6_sepconv3_bn (BatchNormal (None, 19, 19, 728)  2912        block6_sepconv3[0][0]            
__________________________________________________________________________________________________
add_21 (Add)                    (None, 19, 19, 728)  0           block6_sepconv3_bn[0][0]         
                                                                 add_20[0][0]                     
__________________________________________________________________________________________________
block7_sepconv1_act (Activation (None, 19, 19, 728)  0           add_21[0][0]                     
__________________________________________________________________________________________________
block7_sepconv1 (SeparableConv2 (None, 19, 19, 728)  536536      block7_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv1_bn (BatchNormal (None, 19, 19, 728)  2912        block7_sepconv1[0][0]            
__________________________________________________________________________________________________
block7_sepconv2_act (Activation (None, 19, 19, 728)  0           block7_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block7_sepconv2 (SeparableConv2 (None, 19, 19, 728)  536536      block7_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv2_bn (BatchNormal (None, 19, 19, 728)  2912        block7_sepconv2[0][0]            
__________________________________________________________________________________________________
block7_sepconv3_act (Activation (None, 19, 19, 728)  0           block7_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block7_sepconv3 (SeparableConv2 (None, 19, 19, 728)  536536      block7_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block7_sepconv3_bn (BatchNormal (None, 19, 19, 728)  2912        block7_sepconv3[0][0]            
__________________________________________________________________________________________________
add_22 (Add)                    (None, 19, 19, 728)  0           block7_sepconv3_bn[0][0]         
                                                                 add_21[0][0]                     
__________________________________________________________________________________________________
block8_sepconv1_act (Activation (None, 19, 19, 728)  0           add_22[0][0]                     
__________________________________________________________________________________________________
block8_sepconv1 (SeparableConv2 (None, 19, 19, 728)  536536      block8_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv1_bn (BatchNormal (None, 19, 19, 728)  2912        block8_sepconv1[0][0]            
__________________________________________________________________________________________________
block8_sepconv2_act (Activation (None, 19, 19, 728)  0           block8_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block8_sepconv2 (SeparableConv2 (None, 19, 19, 728)  536536      block8_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv2_bn (BatchNormal (None, 19, 19, 728)  2912        block8_sepconv2[0][0]            
__________________________________________________________________________________________________
block8_sepconv3_act (Activation (None, 19, 19, 728)  0           block8_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block8_sepconv3 (SeparableConv2 (None, 19, 19, 728)  536536      block8_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block8_sepconv3_bn (BatchNormal (None, 19, 19, 728)  2912        block8_sepconv3[0][0]            
__________________________________________________________________________________________________
add_23 (Add)                    (None, 19, 19, 728)  0           block8_sepconv3_bn[0][0]         
                                                                 add_22[0][0]                     
__________________________________________________________________________________________________
block9_sepconv1_act (Activation (None, 19, 19, 728)  0           add_23[0][0]                     
__________________________________________________________________________________________________
block9_sepconv1 (SeparableConv2 (None, 19, 19, 728)  536536      block9_sepconv1_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv1_bn (BatchNormal (None, 19, 19, 728)  2912        block9_sepconv1[0][0]            
__________________________________________________________________________________________________
block9_sepconv2_act (Activation (None, 19, 19, 728)  0           block9_sepconv1_bn[0][0]         
__________________________________________________________________________________________________
block9_sepconv2 (SeparableConv2 (None, 19, 19, 728)  536536      block9_sepconv2_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv2_bn (BatchNormal (None, 19, 19, 728)  2912        block9_sepconv2[0][0]            
__________________________________________________________________________________________________
block9_sepconv3_act (Activation (None, 19, 19, 728)  0           block9_sepconv2_bn[0][0]         
__________________________________________________________________________________________________
block9_sepconv3 (SeparableConv2 (None, 19, 19, 728)  536536      block9_sepconv3_act[0][0]        
__________________________________________________________________________________________________
block9_sepconv3_bn (BatchNormal (None, 19, 19, 728)  2912        block9_sepconv3[0][0]            
__________________________________________________________________________________________________
add_24 (Add)                    (None, 19, 19, 728)  0           block9_sepconv3_bn[0][0]         
                                                                 add_23[0][0]                     
__________________________________________________________________________________________________
block10_sepconv1_act (Activatio (None, 19, 19, 728)  0           add_24[0][0]                     
__________________________________________________________________________________________________
block10_sepconv1 (SeparableConv (None, 19, 19, 728)  536536      block10_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv1_bn (BatchNorma (None, 19, 19, 728)  2912        block10_sepconv1[0][0]           
__________________________________________________________________________________________________
block10_sepconv2_act (Activatio (None, 19, 19, 728)  0           block10_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block10_sepconv2 (SeparableConv (None, 19, 19, 728)  536536      block10_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv2_bn (BatchNorma (None, 19, 19, 728)  2912        block10_sepconv2[0][0]           
__________________________________________________________________________________________________
block10_sepconv3_act (Activatio (None, 19, 19, 728)  0           block10_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block10_sepconv3 (SeparableConv (None, 19, 19, 728)  536536      block10_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block10_sepconv3_bn (BatchNorma (None, 19, 19, 728)  2912        block10_sepconv3[0][0]           
__________________________________________________________________________________________________
add_25 (Add)                    (None, 19, 19, 728)  0           block10_sepconv3_bn[0][0]        
                                                                 add_24[0][0]                     
__________________________________________________________________________________________________
block11_sepconv1_act (Activatio (None, 19, 19, 728)  0           add_25[0][0]                     
__________________________________________________________________________________________________
block11_sepconv1 (SeparableConv (None, 19, 19, 728)  536536      block11_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv1_bn (BatchNorma (None, 19, 19, 728)  2912        block11_sepconv1[0][0]           
__________________________________________________________________________________________________
block11_sepconv2_act (Activatio (None, 19, 19, 728)  0           block11_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block11_sepconv2 (SeparableConv (None, 19, 19, 728)  536536      block11_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv2_bn (BatchNorma (None, 19, 19, 728)  2912        block11_sepconv2[0][0]           
__________________________________________________________________________________________________
block11_sepconv3_act (Activatio (None, 19, 19, 728)  0           block11_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block11_sepconv3 (SeparableConv (None, 19, 19, 728)  536536      block11_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block11_sepconv3_bn (BatchNorma (None, 19, 19, 728)  2912        block11_sepconv3[0][0]           
__________________________________________________________________________________________________
add_26 (Add)                    (None, 19, 19, 728)  0           block11_sepconv3_bn[0][0]        
                                                                 add_25[0][0]                     
__________________________________________________________________________________________________
block12_sepconv1_act (Activatio (None, 19, 19, 728)  0           add_26[0][0]                     
__________________________________________________________________________________________________
block12_sepconv1 (SeparableConv (None, 19, 19, 728)  536536      block12_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv1_bn (BatchNorma (None, 19, 19, 728)  2912        block12_sepconv1[0][0]           
__________________________________________________________________________________________________
block12_sepconv2_act (Activatio (None, 19, 19, 728)  0           block12_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block12_sepconv2 (SeparableConv (None, 19, 19, 728)  536536      block12_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv2_bn (BatchNorma (None, 19, 19, 728)  2912        block12_sepconv2[0][0]           
__________________________________________________________________________________________________
block12_sepconv3_act (Activatio (None, 19, 19, 728)  0           block12_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
block12_sepconv3 (SeparableConv (None, 19, 19, 728)  536536      block12_sepconv3_act[0][0]       
__________________________________________________________________________________________________
block12_sepconv3_bn (BatchNorma (None, 19, 19, 728)  2912        block12_sepconv3[0][0]           
__________________________________________________________________________________________________
add_27 (Add)                    (None, 19, 19, 728)  0           block12_sepconv3_bn[0][0]        
                                                                 add_26[0][0]                     
__________________________________________________________________________________________________
block13_sepconv1_act (Activatio (None, 19, 19, 728)  0           add_27[0][0]                     
__________________________________________________________________________________________________
block13_sepconv1 (SeparableConv (None, 19, 19, 728)  536536      block13_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block13_sepconv1_bn (BatchNorma (None, 19, 19, 728)  2912        block13_sepconv1[0][0]           
__________________________________________________________________________________________________
block13_sepconv2_act (Activatio (None, 19, 19, 728)  0           block13_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block13_sepconv2 (SeparableConv (None, 19, 19, 1024) 752024      block13_sepconv2_act[0][0]       
__________________________________________________________________________________________________
block13_sepconv2_bn (BatchNorma (None, 19, 19, 1024) 4096        block13_sepconv2[0][0]           
__________________________________________________________________________________________________
conv2d_286 (Conv2D)             (None, 10, 10, 1024) 745472      add_27[0][0]                     
__________________________________________________________________________________________________
block13_pool (MaxPooling2D)     (None, 10, 10, 1024) 0           block13_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
batch_normalization_286 (BatchN (None, 10, 10, 1024) 4096        conv2d_286[0][0]                 
__________________________________________________________________________________________________
add_28 (Add)                    (None, 10, 10, 1024) 0           block13_pool[0][0]               
                                                                 batch_normalization_286[0][0]    
__________________________________________________________________________________________________
block14_sepconv1 (SeparableConv (None, 10, 10, 1536) 1582080     add_28[0][0]                     
__________________________________________________________________________________________________
block14_sepconv1_bn (BatchNorma (None, 10, 10, 1536) 6144        block14_sepconv1[0][0]           
__________________________________________________________________________________________________
block14_sepconv1_act (Activatio (None, 10, 10, 1536) 0           block14_sepconv1_bn[0][0]        
__________________________________________________________________________________________________
block14_sepconv2 (SeparableConv (None, 10, 10, 2048) 3159552     block14_sepconv1_act[0][0]       
__________________________________________________________________________________________________
block14_sepconv2_bn (BatchNorma (None, 10, 10, 2048) 8192        block14_sepconv2[0][0]           
__________________________________________________________________________________________________
block14_sepconv2_act (Activatio (None, 10, 10, 2048) 0           block14_sepconv2_bn[0][0]        
__________________________________________________________________________________________________
global_average_pooling2d_5 (Glo (None, 2048)         0           block14_sepconv2_act[0][0]       
__________________________________________________________________________________________________
dropout_5 (Dropout)             (None, 2048)         0           global_average_pooling2d_5[0][0] 
__________________________________________________________________________________________________
dense_5 (Dense)                 (None, 1)            2049        dropout_5[0][0]                  
==================================================================================================
Total params: 20,863,529
Trainable params: 2,049
Non-trainable params: 20,861,480
__________________________________________________________________________________________________

earlystop = EarlyStopping(monitor='val_loss', patience=5, verbose=0, mode='auto')

model_Xception.compile(loss = 'binary_crossentropy', optimizer = 'Adam', metrics =['accuracy'])
model_Xception_history = model_Xception.fit_generator(train_generator(X_train, y_train, batch_size=batch_size),
                                                    steps_per_epoch=len(y_train)//batch_size, epochs=epochs,
                                                    validation_data = val_generator(X_val, y_val, batch_size=batch_size),
                                                    validation_steps=len(y_val)//batch_size,
                                                    callbacks = [earlystop],
                                                    verbose=2)

Epoch 1/10
 - 367s - loss: 0.1356 - acc: 0.9645 - val_loss: 0.0901 - val_acc: 0.9768
Epoch 2/10
 - 364s - loss: 0.0630 - acc: 0.9799 - val_loss: 0.0783 - val_acc: 0.9776
Epoch 3/10
 - 364s - loss: 0.0546 - acc: 0.9820 - val_loss: 0.0801 - val_acc: 0.9764
Epoch 4/10
 - 364s - loss: 0.0487 - acc: 0.9829 - val_loss: 0.0758 - val_acc: 0.9774
Epoch 5/10
 - 364s - loss: 0.0490 - acc: 0.9825 - val_loss: 0.0791 - val_acc: 0.9756
Epoch 6/10
 - 364s - loss: 0.0472 - acc: 0.9834 - val_loss: 0.0722 - val_acc: 0.9780
Epoch 7/10
 - 363s - loss: 0.0447 - acc: 0.9843 - val_loss: 0.0696 - val_acc: 0.9798
Epoch 8/10
 - 364s - loss: 0.0438 - acc: 0.9839 - val_loss: 0.0754 - val_acc: 0.9772
Epoch 9/10
 - 364s - loss: 0.0444 - acc: 0.9840 - val_loss: 0.0729 - val_acc: 0.9784
Epoch 10/10
 - 363s - loss: 0.0424 - acc: 0.9848 - val_loss: 0.0734 - val_acc: 0.9780

from matplotlib import pyplot as plt  
history=model_Xception_history  
# summarize history for accuracy
plt.plot(history.history['acc'])  
plt.plot(history.history['val_acc'])
plt.title('model accuracy')  
plt.ylabel('accuracy')  
plt.xlabel('epoch')  
plt.grid()
plt.legend(['train', 'test'], loc='lower right')  
plt.show()  
# summarize history for loss  
plt.plot(history.history['loss'])  
plt.plot(history.history['val_loss'])  
plt.title('model loss')  
plt.ylabel('loss')  
plt.xlabel('epoch')  
plt.grid()
plt.legend(['train', 'test'], loc='upper right')  
plt.show()  

# test generator
n_test = 12500
X_test = np.zeros((n_test,299,299,3),dtype=np.uint8)
for i in tqdm(range(12500)):
    j = i+1
    X_test[i] = cv2.resize(cv2.imread('test/test/%d.jpg' % j), (299,299))
    
def test_generator(X, batch_size): 
    datalen = len(X)
    counter = datalen//batch_size
    while (True):
        for i in range(counter):
            yield (X[i * batch_size:(i + 1) * batch_size]-127.5)/127.5

# make prediction
# clip log-loss results to range(0.005,0.995)
predictions = model_InceptionV3_GAP.predict_generator(test_generator(X_test,100),steps=125, verbose=1)
predictions = predictions.clip(min=0.005,max=0.995)
output = pd.read_csv('sample_submission.csv')
print(len(predictions))
output.label = predictions
output.to_csv('InceptionV3_predictions.csv',index=None)